id	sid	tid	token	lemma	pos
cuesj-252	1	1	tx_1	tx_1	PROPN
cuesj-252	1	2	~	~	X
cuesj-252	1	3	abs	ab	NOUN
cuesj-252	1	4	:	:	PUNCT
cuesj-252	1	5	at	at	ADP
cuesj-252	1	6	/	/	SYM
cuesj-252	1	7	add	add	VERB
cuesj-252	1	8	:	:	PUNCT
cuesj-252	1	9	tx_2	tx_2	PROPN
cuesj-252	1	10	~	~	NOUN
cuesj-252	1	11	abs	ab	NOUN
cuesj-252	1	12	:	:	PUNCT
cuesj-252	1	13	at	at	ADP
cuesj-252	1	14	9	9	NUM
cuesj-252	1	15	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-252	1	16	cuesj	cuesj	NOUN
cuesj-252	1	17	2020	2020	NUM
cuesj-252	1	18	,	,	PUNCT
cuesj-252	1	19	4	4	NUM
cuesj-252	1	20	(	(	PUNCT
cuesj-252	1	21	2	2	NUM
cuesj-252	1	22	):	):	PUNCT
cuesj-252	1	23	9	9	NUM
cuesj-252	1	24	-	-	SYM
cuesj-252	1	25	12	12	NUM
cuesj-252	1	26	research	research	NOUN
cuesj-252	1	27	article	article	NOUN
cuesj-252	1	28	likelihood	likelihood	NOUN
cuesj-252	1	29	approach	approach	NOUN
cuesj-252	1	30	for	for	ADP
cuesj-252	1	31	bayesian	bayesian	NOUN
cuesj-252	1	32	logistic	logistic	NOUN
cuesj-252	1	33	weighted	weight	VERB
cuesj-252	1	34	model	model	NOUN
cuesj-252	1	35	:	:	PUNCT
cuesj-252	1	36	missing	miss	VERB
cuesj-252	1	37	completely	completely	ADV
cuesj-252	1	38	at	at	ADP
cuesj-252	1	39	random	random	ADJ
cuesj-252	1	40	case	case	NOUN
cuesj-252	1	41	dler	dler	NOUN
cuesj-252	1	42	h.	h.	PROPN
cuesj-252	1	43	kadir	kadir	PROPN
cuesj-252	1	44	*	*	PROPN
cuesj-252	1	45	department	department	PROPN
cuesj-252	1	46	of	of	ADP
cuesj-252	1	47	statistics	statistic	NOUN
cuesj-252	1	48	,	,	PUNCT
cuesj-252	1	49	college	college	NOUN
cuesj-252	1	50	of	of	ADP
cuesj-252	1	51	administration	administration	NOUN
cuesj-252	1	52	and	and	CCONJ
cuesj-252	1	53	economics	economic	NOUN
cuesj-252	1	54	,	,	PUNCT
cuesj-252	1	55	salahaddin	salahaddin	VERB
cuesj-252	1	56	university	university	NOUN
cuesj-252	1	57	-	-	PUNCT
cuesj-252	1	58	erbil	erbil	PROPN
cuesj-252	1	59	,	,	PUNCT
cuesj-252	1	60	kurdistan	kurdistan	PROPN
cuesj-252	1	61	region	region	PROPN
cuesj-252	2	1	f.r	f.r	PROPN
cuesj-252	2	2	.	.	PROPN
cuesj-252	2	3	iraq	iraq	PROPN
cuesj-252	2	4	abstract	abstract	PROPN
cuesj-252	2	5	increasing	increase	VERB
cuesj-252	2	6	the	the	DET
cuesj-252	2	7	response	response	NOUN
cuesj-252	2	8	rate	rate	NOUN
cuesj-252	2	9	and	and	CCONJ
cuesj-252	2	10	minimizing	minimize	VERB
cuesj-252	2	11	non	non	ADJ
cuesj-252	2	12	-	-	ADJ
cuesj-252	2	13	response	response	ADJ
cuesj-252	2	14	rates	rate	NOUN
cuesj-252	2	15	represent	represent	VERB
cuesj-252	2	16	the	the	DET
cuesj-252	2	17	primary	primary	ADJ
cuesj-252	2	18	challenges	challenge	NOUN
cuesj-252	2	19	facing	face	VERB
cuesj-252	2	20	researchers	researcher	NOUN
cuesj-252	2	21	performing	perform	VERB
cuesj-252	2	22	longitudinal	longitudinal	ADJ
cuesj-252	2	23	and	and	CCONJ
cuesj-252	2	24	cohort	cohort	NOUN
cuesj-252	2	25	research	research	NOUN
cuesj-252	2	26	,	,	PUNCT
cuesj-252	2	27	especially	especially	ADV
cuesj-252	2	28	can	can	AUX
cuesj-252	2	29	be	be	AUX
cuesj-252	2	30	seen	see	VERB
cuesj-252	2	31	in	in	ADP
cuesj-252	2	32	the	the	DET
cuesj-252	2	33	area	area	NOUN
cuesj-252	2	34	of	of	ADP
cuesj-252	2	35	pediatric	pediatric	ADJ
cuesj-252	2	36	medicine	medicine	NOUN
cuesj-252	2	37	.	.	PUNCT
cuesj-252	3	1	when	when	SCONJ
cuesj-252	3	2	there	there	PRON
cuesj-252	3	3	are	be	VERB
cuesj-252	3	4	missing	miss	VERB
cuesj-252	3	5	data	datum	NOUN
cuesj-252	3	6	,	,	PUNCT
cuesj-252	3	7	complete	complete	ADJ
cuesj-252	3	8	case	case	NOUN
cuesj-252	3	9	analysis	analysis	NOUN
cuesj-252	3	10	makes	make	VERB
cuesj-252	3	11	findings	finding	NOUN
cuesj-252	3	12	bias	bias	VERB
cuesj-252	3	13	.	.	PUNCT
cuesj-252	4	1	inverse	inverse	NOUN
cuesj-252	4	2	probability	probability	NOUN
cuesj-252	4	3	weighting	weighting	NOUN
cuesj-252	4	4	(	(	PUNCT
cuesj-252	4	5	ipw	ipw	PROPN
cuesj-252	4	6	)	)	PUNCT
cuesj-252	4	7	is	be	AUX
cuesj-252	4	8	one	one	NUM
cuesj-252	4	9	of	of	ADP
cuesj-252	4	10	the	the	DET
cuesj-252	4	11	many	many	ADJ
cuesj-252	4	12	available	available	ADJ
cuesj-252	4	13	approaches	approach	NOUN
cuesj-252	4	14	for	for	ADP
cuesj-252	4	15	reducing	reduce	VERB
cuesj-252	4	16	bias	bias	NOUN
cuesj-252	4	17	using	use	VERB
cuesj-252	4	18	complete	complete	ADJ
cuesj-252	4	19	case	case	NOUN
cuesj-252	4	20	analysis	analysis	NOUN
cuesj-252	4	21	.	.	PUNCT
cuesj-252	5	1	here	here	ADV
cuesj-252	5	2	,	,	PUNCT
cuesj-252	5	3	a	a	DET
cuesj-252	5	4	complete	complete	ADJ
cuesj-252	5	5	case	case	NOUN
cuesj-252	5	6	is	be	AUX
cuesj-252	5	7	weighted	weight	VERB
cuesj-252	5	8	by	by	ADP
cuesj-252	5	9	probability	probability	NOUN
cuesj-252	5	10	inverse	inverse	NOUN
cuesj-252	5	11	of	of	ADP
cuesj-252	5	12	complete	complete	ADJ
cuesj-252	5	13	cases	case	NOUN
cuesj-252	5	14	.	.	PUNCT
cuesj-252	6	1	the	the	DET
cuesj-252	6	2	data	datum	NOUN
cuesj-252	6	3	were	be	AUX
cuesj-252	6	4	collected	collect	VERB
cuesj-252	6	5	from	from	ADP
cuesj-252	6	6	the	the	DET
cuesj-252	6	7	neonatal	neonatal	ADJ
cuesj-252	6	8	intensive	intensive	ADJ
cuesj-252	6	9	care	care	NOUN
cuesj-252	6	10	unit	unit	NOUN
cuesj-252	6	11	at	at	ADP
cuesj-252	6	12	erbil	erbil	PROPN
cuesj-252	6	13	maternity	maternity	PROPN
cuesj-252	6	14	hospital	hospital	NOUN
cuesj-252	6	15	from	from	ADP
cuesj-252	6	16	2012	2012	NUM
cuesj-252	6	17	to	to	ADP
cuesj-252	6	18	2017	2017	NUM
cuesj-252	6	19	.	.	PUNCT
cuesj-252	7	1	in	in	ADP
cuesj-252	7	2	total	total	ADJ
cuesj-252	7	3	,	,	PUNCT
cuesj-252	7	4	570	570	NUM
cuesj-252	7	5	babies	baby	NOUN
cuesj-252	7	6	(	(	PUNCT
cuesj-252	7	7	288	288	NUM
cuesj-252	7	8	male	male	NOUN
cuesj-252	7	9	and	and	CCONJ
cuesj-252	7	10	282	282	NUM
cuesj-252	7	11	females	female	NOUN
cuesj-252	7	12	)	)	PUNCT
cuesj-252	7	13	were	be	AUX
cuesj-252	7	14	born	bear	VERB
cuesj-252	7	15	very	very	ADV
cuesj-252	7	16	preterm	preterm	ADJ
cuesj-252	7	17	.	.	PUNCT
cuesj-252	8	1	the	the	DET
cuesj-252	8	2	aim	aim	NOUN
cuesj-252	8	3	of	of	ADP
cuesj-252	8	4	this	this	DET
cuesj-252	8	5	paper	paper	NOUN
cuesj-252	8	6	is	be	AUX
cuesj-252	8	7	to	to	PART
cuesj-252	8	8	use	use	VERB
cuesj-252	8	9	ipw	ipw	PROPN
cuesj-252	8	10	on	on	ADP
cuesj-252	8	11	the	the	DET
cuesj-252	8	12	bayesian	bayesian	NOUN
cuesj-252	8	13	logistic	logistic	ADJ
cuesj-252	8	14	model	model	NOUN
cuesj-252	8	15	developmental	developmental	ADJ
cuesj-252	8	16	outcome	outcome	NOUN
cuesj-252	8	17	.	.	PUNCT
cuesj-252	9	1	the	the	DET
cuesj-252	9	2	mental	mental	PROPN
cuesj-252	9	3	development	development	PROPN
cuesj-252	9	4	index	index	NOUN
cuesj-252	9	5	approach	approach	NOUN
cuesj-252	9	6	was	be	AUX
cuesj-252	9	7	used	use	VERB
cuesj-252	9	8	for	for	ADP
cuesj-252	9	9	assessing	assess	VERB
cuesj-252	9	10	the	the	DET
cuesj-252	9	11	cognitive	cognitive	ADJ
cuesj-252	9	12	development	development	NOUN
cuesj-252	9	13	of	of	ADP
cuesj-252	9	14	those	those	PRON
cuesj-252	9	15	born	bear	VERB
cuesj-252	9	16	very	very	ADV
cuesj-252	9	17	preterm	preterm	ADJ
cuesj-252	9	18	.	.	PUNCT
cuesj-252	10	1	almost	almost	ADV
cuesj-252	10	2	half	half	NOUN
cuesj-252	10	3	of	of	ADP
cuesj-252	10	4	the	the	DET
cuesj-252	10	5	information	information	NOUN
cuesj-252	10	6	for	for	ADP
cuesj-252	10	7	the	the	DET
cuesj-252	10	8	babies	baby	NOUN
cuesj-252	10	9	was	be	AUX
cuesj-252	10	10	missing	miss	VERB
cuesj-252	10	11	,	,	PUNCT
cuesj-252	10	12	meaning	mean	VERB
cuesj-252	10	13	that	that	SCONJ
cuesj-252	10	14	we	we	PRON
cuesj-252	10	15	do	do	AUX
cuesj-252	10	16	not	not	PART
cuesj-252	10	17	know	know	VERB
cuesj-252	10	18	whether	whether	SCONJ
cuesj-252	10	19	they	they	PRON
cuesj-252	10	20	have	have	VERB
cuesj-252	10	21	cognitive	cognitive	ADJ
cuesj-252	10	22	development	development	NOUN
cuesj-252	10	23	issues	issue	NOUN
cuesj-252	10	24	.	.	PUNCT
cuesj-252	11	1	we	we	PRON
cuesj-252	11	2	obtained	obtain	VERB
cuesj-252	11	3	greater	great	ADJ
cuesj-252	11	4	precision	precision	NOUN
cuesj-252	11	5	in	in	ADP
cuesj-252	11	6	results	result	NOUN
cuesj-252	11	7	and	and	CCONJ
cuesj-252	11	8	standard	standard	ADJ
cuesj-252	11	9	deviation	deviation	NOUN
cuesj-252	11	10	of	of	ADP
cuesj-252	11	11	parameter	parameter	NOUN
cuesj-252	11	12	estimates	estimate	NOUN
cuesj-252	11	13	which	which	PRON
cuesj-252	11	14	are	be	AUX
cuesj-252	11	15	less	less	ADJ
cuesj-252	11	16	in	in	ADP
cuesj-252	11	17	the	the	DET
cuesj-252	11	18	posterior	posterior	NOUN
cuesj-252	11	19	weighted	weight	VERB
cuesj-252	11	20	model	model	NOUN
cuesj-252	11	21	in	in	ADP
cuesj-252	11	22	comparison	comparison	NOUN
cuesj-252	11	23	with	with	ADP
cuesj-252	11	24	frequent	frequent	ADJ
cuesj-252	11	25	analysis	analysis	NOUN
cuesj-252	11	26	.	.	PUNCT
cuesj-252	12	1	further	far	ADV
cuesj-252	12	2	,	,	PUNCT
cuesj-252	12	3	research	research	NOUN
cuesj-252	12	4	is	be	AUX
cuesj-252	12	5	needed	need	VERB
cuesj-252	12	6	using	use	VERB
cuesj-252	12	7	methods	method	NOUN
cuesj-252	12	8	such	such	ADJ
cuesj-252	12	9	as	as	ADP
cuesj-252	12	10	bootstrapping	bootstrappe	VERB
cuesj-252	12	11	,	,	PUNCT
cuesj-252	12	12	sandwich	sandwich	NOUN
cuesj-252	12	13	,	,	PUNCT
cuesj-252	12	14	resampling	resample	VERB
cuesj-252	12	15	,	,	PUNCT
cuesj-252	12	16	and	and	CCONJ
cuesj-252	12	17	jackknife	jackknife	NOUN
cuesj-252	12	18	methods	method	NOUN
cuesj-252	12	19	for	for	ADP
cuesj-252	12	20	dealing	deal	VERB
cuesj-252	12	21	with	with	ADP
cuesj-252	12	22	missing	miss	VERB
cuesj-252	12	23	data	datum	NOUN
cuesj-252	12	24	.	.	PUNCT
cuesj-252	13	1	keywords	keyword	NOUN
cuesj-252	13	2	:	:	PUNCT
cuesj-252	13	3	likelihood	likelihood	NOUN
cuesj-252	13	4	,	,	PUNCT
cuesj-252	13	5	logistic	logistic	ADJ
cuesj-252	13	6	weighting	weighting	NOUN
cuesj-252	13	7	,	,	PUNCT
cuesj-252	13	8	missing	miss	VERB
cuesj-252	13	9	data	datum	NOUN
cuesj-252	13	10	,	,	PUNCT
cuesj-252	13	11	preterm	preterm	ADJ
cuesj-252	13	12	infants	infant	NOUN
cuesj-252	13	13	introduction	introduction	NOUN
cuesj-252	13	14	increasing	increase	VERB
cuesj-252	13	15	the	the	DET
cuesj-252	13	16	response	response	NOUN
cuesj-252	13	17	rate	rate	NOUN
cuesj-252	13	18	and	and	CCONJ
cuesj-252	13	19	minimizing	minimize	VERB
cuesj-252	13	20	non	non	ADJ
cuesj-252	13	21	-	-	ADJ
cuesj-252	13	22	response	response	ADJ
cuesj-252	13	23	rates	rate	NOUN
cuesj-252	13	24	represent	represent	VERB
cuesj-252	13	25	the	the	DET
cuesj-252	13	26	primary	primary	ADJ
cuesj-252	13	27	challenges	challenge	NOUN
cuesj-252	13	28	facing	face	VERB
cuesj-252	13	29	researchers	researcher	NOUN
cuesj-252	13	30	performing	perform	VERB
cuesj-252	13	31	longitudinal	longitudinal	ADJ
cuesj-252	13	32	and	and	CCONJ
cuesj-252	13	33	cohort	cohort	NOUN
cuesj-252	13	34	research	research	NOUN
cuesj-252	13	35	.	.	PUNCT
cuesj-252	14	1	this	this	PRON
cuesj-252	14	2	can	can	AUX
cuesj-252	14	3	especially	especially	ADV
cuesj-252	14	4	be	be	AUX
cuesj-252	14	5	seen	see	VERB
cuesj-252	14	6	in	in	ADP
cuesj-252	14	7	the	the	DET
cuesj-252	14	8	area	area	NOUN
cuesj-252	14	9	of	of	ADP
cuesj-252	14	10	pediatric	pediatric	ADJ
cuesj-252	14	11	medicine	medicine	NOUN
cuesj-252	14	12	,	,	PUNCT
cuesj-252	14	13	whereby	whereby	SCONJ
cuesj-252	14	14	birth	birth	NOUN
cuesj-252	14	15	cohorts	cohort	NOUN
cuesj-252	14	16	are	be	AUX
cuesj-252	14	17	often	often	ADV
cuesj-252	14	18	utilized	utilize	VERB
cuesj-252	14	19	for	for	ADP
cuesj-252	14	20	epidemiological	epidemiological	ADJ
cuesj-252	14	21	research	research	NOUN
cuesj-252	14	22	and	and	CCONJ
cuesj-252	14	23	randomized	randomize	VERB
cuesj-252	14	24	clinical	clinical	ADJ
cuesj-252	14	25	trials	trial	NOUN
cuesj-252	14	26	of	of	ADP
cuesj-252	14	27	parental	parental	ADJ
cuesj-252	14	28	interventions	intervention	NOUN
cuesj-252	14	29	.	.	PUNCT
cuesj-252	15	1	the	the	DET
cuesj-252	15	2	contrition	contrition	NOUN
cuesj-252	15	3	of	of	ADP
cuesj-252	15	4	participants	participant	NOUN
cuesj-252	15	5	lowers	lower	VERB
cuesj-252	15	6	the	the	DET
cuesj-252	15	7	strength	strength	NOUN
cuesj-252	15	8	of	of	ADP
cuesj-252	15	9	the	the	DET
cuesj-252	15	10	research	research	NOUN
cuesj-252	15	11	,	,	PUNCT
cuesj-252	15	12	as	as	ADV
cuesj-252	15	13	well	well	ADV
cuesj-252	15	14	as	as	ADP
cuesj-252	15	15	leading	lead	VERB
cuesj-252	15	16	to	to	ADP
cuesj-252	15	17	bias	bias	NOUN
cuesj-252	15	18	in	in	ADP
cuesj-252	15	19	the	the	DET
cuesj-252	15	20	results.[1	results.[1	NOUN
cuesj-252	15	21	]	]	PUNCT
cuesj-252	15	22	a	a	DET
cuesj-252	15	23	non	non	ADJ
cuesj-252	15	24	-	-	NOUN
cuesj-252	15	25	response	response	NOUN
cuesj-252	15	26	usually	usually	ADV
cuesj-252	15	27	has	have	VERB
cuesj-252	15	28	more	more	ADJ
cuesj-252	15	29	medical	medical	ADJ
cuesj-252	15	30	and	and	CCONJ
cuesj-252	15	31	socioeconomic	socioeconomic	ADJ
cuesj-252	15	32	risks	risk	NOUN
cuesj-252	15	33	and	and	CCONJ
cuesj-252	15	34	can	can	AUX
cuesj-252	15	35	have	have	VERB
cuesj-252	15	36	systematic	systematic	ADJ
cuesj-252	15	37	variations	variation	NOUN
cuesj-252	15	38	regarding	regard	VERB
cuesj-252	15	39	interest	interest	NOUN
cuesj-252	15	40	disorders	disorder	NOUN
cuesj-252	15	41	,	,	PUNCT
cuesj-252	15	42	causing	cause	VERB
cuesj-252	15	43	a	a	DET
cuesj-252	15	44	biased	biased	ADJ
cuesj-252	15	45	estimate	estimate	NOUN
cuesj-252	15	46	of	of	ADP
cuesj-252	15	47	an	an	DET
cuesj-252	15	48	adverse	adverse	ADJ
cuesj-252	15	49	outcome.[2	outcome.[2	NOUN
cuesj-252	15	50	]	]	PUNCT
cuesj-252	15	51	it	it	PRON
cuesj-252	15	52	is	be	AUX
cuesj-252	15	53	also	also	ADV
cuesj-252	15	54	frequently	frequently	ADV
cuesj-252	15	55	the	the	DET
cuesj-252	15	56	case	case	NOUN
cuesj-252	15	57	that	that	SCONJ
cuesj-252	15	58	data	datum	NOUN
cuesj-252	15	59	are	be	AUX
cuesj-252	15	60	missing	miss	VERB
cuesj-252	15	61	in	in	ADP
cuesj-252	15	62	social	social	ADJ
cuesj-252	15	63	research	research	NOUN
cuesj-252	15	64	.	.	PUNCT
cuesj-252	16	1	they	they	PRON
cuesj-252	16	2	present	present	VERB
cuesj-252	16	3	ambiguities	ambiguity	NOUN
cuesj-252	16	4	in	in	ADP
cuesj-252	16	5	statistical	statistical	ADJ
cuesj-252	16	6	analyses	analysis	NOUN
cuesj-252	16	7	of	of	ADP
cuesj-252	16	8	a	a	DET
cuesj-252	16	9	different	different	ADJ
cuesj-252	16	10	type	type	NOUN
cuesj-252	16	11	to	to	ADP
cuesj-252	16	12	that	that	PRON
cuesj-252	16	13	of	of	ADP
cuesj-252	16	14	the	the	DET
cuesj-252	16	15	usual	usual	ADJ
cuesj-252	16	16	imprecisions	imprecision	NOUN
cuesj-252	16	17	of	of	ADP
cuesj-252	16	18	samples	sample	NOUN
cuesj-252	16	19	,	,	PUNCT
cuesj-252	16	20	which	which	PRON
cuesj-252	16	21	become	become	VERB
cuesj-252	16	22	lower	low	ADJ
cuesj-252	16	23	with	with	ADP
cuesj-252	16	24	increases	increase	NOUN
cuesj-252	16	25	in	in	ADP
cuesj-252	16	26	sample	sample	NOUN
cuesj-252	16	27	sizes	size	NOUN
cuesj-252	16	28	.	.	PUNCT
cuesj-252	17	1	therefore	therefore	ADV
cuesj-252	17	2	,	,	PUNCT
cuesj-252	17	3	greater	great	ADJ
cuesj-252	17	4	assumptions	assumption	NOUN
cuesj-252	17	5	are	be	AUX
cuesj-252	17	6	required	require	VERB
cuesj-252	17	7	to	to	PART
cuesj-252	17	8	permit	permit	VERB
cuesj-252	17	9	inferences	inference	NOUN
cuesj-252	17	10	to	to	PART
cuesj-252	17	11	be	be	AUX
cuesj-252	17	12	reached	reach	VERB
cuesj-252	17	13	.	.	PUNCT
cuesj-252	18	1	over	over	ADP
cuesj-252	18	2	the	the	DET
cuesj-252	18	3	past	past	ADJ
cuesj-252	18	4	10	10	NUM
cuesj-252	18	5	years	year	NOUN
cuesj-252	18	6	,	,	PUNCT
cuesj-252	18	7	there	there	PRON
cuesj-252	18	8	has	have	AUX
cuesj-252	18	9	been	be	AUX
cuesj-252	18	10	much	much	ADV
cuesj-252	18	11	theoretical	theoretical	ADJ
cuesj-252	18	12	research	research	NOUN
cuesj-252	18	13	into	into	ADP
cuesj-252	18	14	ways	way	NOUN
cuesj-252	18	15	of	of	ADP
cuesj-252	18	16	analyzing	analyze	VERB
cuesj-252	18	17	missing	miss	VERB
cuesj-252	18	18	data	datum	NOUN
cuesj-252	18	19	sets	set	NOUN
cuesj-252	18	20	.	.	PUNCT
cuesj-252	19	1	missing	miss	VERB
cuesj-252	19	2	data	datum	NOUN
cuesj-252	19	3	can	can	AUX
cuesj-252	19	4	be	be	AUX
cuesj-252	19	5	defined	define	VERB
cuesj-252	19	6	as	as	ADP
cuesj-252	19	7	a	a	DET
cuesj-252	19	8	value	value	NOUN
cuesj-252	19	9	that	that	PRON
cuesj-252	19	10	is	be	AUX
cuesj-252	19	11	not	not	PART
cuesj-252	19	12	recorded	record	VERB
cuesj-252	19	13	for	for	ADP
cuesj-252	19	14	a	a	DET
cuesj-252	19	15	variable	variable	NOUN
cuesj-252	19	16	in	in	ADP
cuesj-252	19	17	the	the	DET
cuesj-252	19	18	observation	observation	NOUN
cuesj-252	19	19	of	of	ADP
cuesj-252	19	20	interest	interest	NOUN
cuesj-252	19	21	.	.	PUNCT
cuesj-252	20	1	almost	almost	ADV
cuesj-252	20	2	all	all	DET
cuesj-252	20	3	branches	branch	NOUN
cuesj-252	20	4	of	of	ADP
cuesj-252	20	5	scientific	scientific	ADJ
cuesj-252	20	6	research	research	NOUN
cuesj-252	20	7	face	face	VERB
cuesj-252	20	8	this	this	DET
cuesj-252	20	9	issue	issue	NOUN
cuesj-252	20	10	and	and	CCONJ
cuesj-252	20	11	will	will	AUX
cuesj-252	20	12	occasionally	occasionally	ADV
cuesj-252	20	13	have	have	VERB
cuesj-252	20	14	to	to	PART
cuesj-252	20	15	deal	deal	VERB
cuesj-252	20	16	with	with	ADP
cuesj-252	20	17	missing	miss	VERB
cuesj-252	20	18	data	datum	NOUN
cuesj-252	20	19	.	.	PUNCT
cuesj-252	21	1	frequently	frequently	ADV
cuesj-252	21	2	,	,	PUNCT
cuesj-252	21	3	the	the	DET
cuesj-252	21	4	missing	miss	VERB
cuesj-252	21	5	data	datum	NOUN
cuesj-252	21	6	appear	appear	VERB
cuesj-252	21	7	as	as	ADP
cuesj-252	21	8	incomplete	incomplete	ADJ
cuesj-252	21	9	data	datum	NOUN
cuesj-252	21	10	on	on	ADP
cuesj-252	21	11	a	a	DET
cuesj-252	21	12	subject	subject	NOUN
cuesj-252	21	13	.	.	PUNCT
cuesj-252	22	1	usually	usually	ADV
cuesj-252	22	2	,	,	PUNCT
cuesj-252	22	3	the	the	DET
cuesj-252	22	4	following	follow	VERB
cuesj-252	22	5	analysis	analysis	NOUN
cuesj-252	22	6	uses	use	VERB
cuesj-252	22	7	only	only	ADV
cuesj-252	22	8	a	a	DET
cuesj-252	22	9	subject	subject	NOUN
cuesj-252	22	10	with	with	ADP
cuesj-252	22	11	a	a	DET
cuesj-252	22	12	complete	complete	ADJ
cuesj-252	22	13	case	case	NOUN
cuesj-252	22	14	measurement	measurement	NOUN
cuesj-252	22	15	(	(	PUNCT
cuesj-252	22	16	complete	complete	ADJ
cuesj-252	22	17	case	case	NOUN
cuesj-252	22	18	analysis	analysis	NOUN
cuesj-252	22	19	)	)	PUNCT
cuesj-252	22	20	.	.	PUNCT
cuesj-252	23	1	this	this	PRON
cuesj-252	23	2	proves	prove	VERB
cuesj-252	23	3	expensive	expensive	ADJ
cuesj-252	23	4	not	not	PART
cuesj-252	23	5	only	only	ADV
cuesj-252	23	6	with	with	ADP
cuesj-252	23	7	regard	regard	NOUN
cuesj-252	23	8	to	to	ADP
cuesj-252	23	9	reductions	reduction	NOUN
cuesj-252	23	10	in	in	ADP
cuesj-252	23	11	sample	sample	NOUN
cuesj-252	23	12	sizes	size	NOUN
cuesj-252	23	13	,	,	PUNCT
cuesj-252	23	14	as	as	ADP
cuesj-252	23	15	an	an	DET
cuesj-252	23	16	unclear	unclear	ADJ
cuesj-252	23	17	variance	variance	NOUN
cuesj-252	23	18	estimate	estimate	NOUN
cuesj-252	23	19	,	,	PUNCT
cuesj-252	23	20	lower	low	ADJ
cuesj-252	23	21	statistical	statistical	ADJ
cuesj-252	23	22	power	power	NOUN
cuesj-252	23	23	,	,	PUNCT
cuesj-252	23	24	and	and	CCONJ
cuesj-252	23	25	the	the	DET
cuesj-252	23	26	parameters	parameter	NOUN
cuesj-252	23	27	which	which	PRON
cuesj-252	23	28	are	be	AUX
cuesj-252	23	29	thought	think	VERB
cuesj-252	23	30	to	to	PART
cuesj-252	23	31	be	be	AUX
cuesj-252	23	32	possibly	possibly	ADV
cuesj-252	23	33	biased	bias	VERB
cuesj-252	23	34	until	until	SCONJ
cuesj-252	23	35	a	a	DET
cuesj-252	23	36	complete	complete	ADJ
cuesj-252	23	37	case	case	NOUN
cuesj-252	23	38	analysis	analysis	NOUN
cuesj-252	23	39	represents	represent	VERB
cuesj-252	23	40	a	a	DET
cuesj-252	23	41	random	random	ADJ
cuesj-252	23	42	sampling	sampling	NOUN
cuesj-252	23	43	of	of	ADP
cuesj-252	23	44	the	the	DET
cuesj-252	23	45	focus	focus	NOUN
cuesj-252	23	46	population	population	NOUN
cuesj-252	23	47	.	.	PUNCT
cuesj-252	24	1	to	to	PART
cuesj-252	24	2	ensure	ensure	VERB
cuesj-252	24	3	that	that	DET
cuesj-252	24	4	bias	bias	NOUN
cuesj-252	24	5	is	be	AUX
cuesj-252	24	6	considered	consider	VERB
cuesj-252	24	7	,	,	PUNCT
cuesj-252	24	8	it	it	PRON
cuesj-252	24	9	is	be	AUX
cuesj-252	24	10	important	important	ADJ
cuesj-252	24	11	to	to	PART
cuesj-252	24	12	understand	understand	VERB
cuesj-252	24	13	the	the	DET
cuesj-252	24	14	mechanisms	mechanism	NOUN
cuesj-252	24	15	and	and	CCONJ
cuesj-252	24	16	the	the	DET
cuesj-252	24	17	patterns	pattern	NOUN
cuesj-252	24	18	of	of	ADP
cuesj-252	24	19	the	the	DET
cuesj-252	24	20	missing	miss	VERB
cuesj-252	24	21	data	datum	NOUN
cuesj-252	24	22	relevant	relevant	ADJ
cuesj-252	24	23	to	to	ADP
cuesj-252	24	24	the	the	DET
cuesj-252	24	25	research	research	NOUN
cuesj-252	24	26	.	.	PUNCT
cuesj-252	25	1	the	the	DET
cuesj-252	25	2	missing	miss	VERB
cuesj-252	25	3	data	datum	NOUN
cuesj-252	25	4	mechanisms	mechanism	NOUN
cuesj-252	25	5	,	,	PUNCT
cuesj-252	25	6	as	as	SCONJ
cuesj-252	25	7	stated	state	VERB
cuesj-252	25	8	by	by	ADP
cuesj-252	25	9	rubin	rubin	PROPN
cuesj-252	25	10	,	,	PUNCT
cuesj-252	25	11	indicate	indicate	VERB
cuesj-252	25	12	the	the	DET
cuesj-252	25	13	link	link	NOUN
cuesj-252	25	14	between	between	ADP
cuesj-252	25	15	the	the	DET
cuesj-252	25	16	missing	miss	VERB
cuesj-252	25	17	values	value	NOUN
cuesj-252	25	18	and	and	CCONJ
cuesj-252	25	19	the	the	DET
cuesj-252	25	20	observed	observe	VERB
cuesj-252	25	21	data.[3	data.[3	NOUN
cuesj-252	25	22	]	]	X
cuesj-252	25	23	it	it	PRON
cuesj-252	25	24	is	be	AUX
cuesj-252	25	25	obvious	obvious	ADJ
cuesj-252	25	26	that	that	PRON
cuesj-252	25	27	bias	bias	NOUN
cuesj-252	25	28	can	can	AUX
cuesj-252	25	29	not	not	PART
cuesj-252	25	30	only	only	ADV
cuesj-252	25	31	occur	occur	VERB
cuesj-252	25	32	when	when	SCONJ
cuesj-252	25	33	there	there	PRON
cuesj-252	25	34	are	be	VERB
cuesj-252	25	35	a	a	DET
cuesj-252	25	36	systematic	systematic	ADJ
cuesj-252	25	37	dropout	dropout	NOUN
cuesj-252	25	38	and	and	CCONJ
cuesj-252	25	39	non	non	ADJ
cuesj-252	25	40	-	-	NOUN
cuesj-252	25	41	response	response	NOUN
cuesj-252	25	42	,	,	PUNCT
cuesj-252	25	43	it	it	PRON
cuesj-252	25	44	can	can	AUX
cuesj-252	25	45	additionally	additionally	ADV
cuesj-252	25	46	stem	stem	VERB
cuesj-252	25	47	from	from	ADP
cuesj-252	25	48	a	a	DET
cuesj-252	25	49	different	different	ADJ
cuesj-252	25	50	sampling	sampling	NOUN
cuesj-252	25	51	probability	probability	NOUN
cuesj-252	25	52	resulting	result	VERB
cuesj-252	25	53	from	from	ADP
cuesj-252	25	54	the	the	DET
cuesj-252	25	55	study	study	NOUN
cuesj-252	25	56	design	design	NOUN
cuesj-252	25	57	.	.	PUNCT
cuesj-252	26	1	a	a	DET
cuesj-252	26	2	non	non	ADJ
cuesj-252	26	3	-	-	ADJ
cuesj-252	26	4	participants	participants	ADJ
cuesj-252	26	5	rate	rate	NOUN
cuesj-252	26	6	of	of	ADP
cuesj-252	26	7	,	,	PUNCT
cuesj-252	26	8	perhaps	perhaps	ADV
cuesj-252	26	9	,	,	PUNCT
cuesj-252	26	10	10	10	NUM
cuesj-252	26	11	%	%	NOUN
cuesj-252	26	12	might	might	AUX
cuesj-252	26	13	not	not	PART
cuesj-252	26	14	produce	produce	VERB
cuesj-252	26	15	a	a	DET
cuesj-252	26	16	stronger	strong	ADJ
cuesj-252	26	17	bias	bias	NOUN
cuesj-252	26	18	unless	unless	SCONJ
cuesj-252	26	19	the	the	DET
cuesj-252	26	20	non	non	NOUN
cuesj-252	26	21	-	-	NOUN
cuesj-252	26	22	response	response	NOUN
cuesj-252	26	23	more	more	ADV
cuesj-252	26	24	powerfully	powerfully	ADV
cuesj-252	26	25	relates	relate	VERB
cuesj-252	26	26	to	to	ADP
cuesj-252	26	27	the	the	DET
cuesj-252	26	28	parameters	parameter	NOUN
cuesj-252	26	29	of	of	ADP
cuesj-252	26	30	interest.[4	interest.[4	NOUN
cuesj-252	26	31	]	]	PUNCT
cuesj-252	26	32	corresponding	correspond	VERB
cuesj-252	26	33	author	author	NOUN
cuesj-252	26	34	:	:	PUNCT
cuesj-252	26	35	dler	dler	PROPN
cuesj-252	26	36	h.	h.	PROPN
cuesj-252	26	37	kadir	kadir	PROPN
cuesj-252	26	38	,	,	PUNCT
cuesj-252	26	39	department	department	PROPN
cuesj-252	26	40	of	of	ADP
cuesj-252	26	41	statistics	statistic	NOUN
cuesj-252	26	42	,	,	PUNCT
cuesj-252	26	43	college	college	NOUN
cuesj-252	26	44	of	of	ADP
cuesj-252	26	45	administration	administration	NOUN
cuesj-252	26	46	and	and	CCONJ
cuesj-252	26	47	economics	economic	NOUN
cuesj-252	26	48	,	,	PUNCT
cuesj-252	26	49	salahaddin	salahaddin	VERB
cuesj-252	26	50	university	university	NOUN
cuesj-252	26	51	-	-	PUNCT
cuesj-252	26	52	erbil	erbil	PROPN
cuesj-252	26	53	,	,	PUNCT
cuesj-252	26	54	kurdistan	kurdistan	PROPN
cuesj-252	26	55	region	region	PROPN
cuesj-252	26	56	f.r	f.r	PROPN
cuesj-252	26	57	.	.	PUNCT
cuesj-252	26	58	iraq	iraq	PROPN
cuesj-252	26	59	.	.	PUNCT
cuesj-252	27	1	e	e	X
cuesj-252	27	2	-	-	NOUN
cuesj-252	27	3	mail	mail	NOUN
cuesj-252	27	4	:	:	PUNCT
cuesj-252	27	5	dler.kadir@su.edu.krd	dler.kadir@su.edu.krd	NOUN
cuesj-252	27	6	doi	doi	NOUN
cuesj-252	27	7	:	:	PUNCT
cuesj-252	27	8	10.24086	10.24086	NUM
cuesj-252	27	9	/	/	SYM
cuesj-252	27	10	cuesj.v4n2y2020.pp9	cuesj.v4n2y2020.pp9	NOUN
cuesj-252	27	11	-	-	PUNCT
cuesj-252	27	12	12	12	NUM
cuesj-252	27	13	copyright	copyright	NOUN
cuesj-252	27	14	©	©	PROPN
cuesj-252	27	15	2020	2020	NUM
cuesj-252	27	16	dler	dler	NOUN
cuesj-252	27	17	h.	h.	PROPN
cuesj-252	27	18	kadir	kadir	PROPN
cuesj-252	27	19	.	.	PUNCT
cuesj-252	28	1	this	this	PRON
cuesj-252	28	2	is	be	AUX
cuesj-252	28	3	an	an	DET
cuesj-252	28	4	open	open	ADJ
cuesj-252	28	5	-	-	PUNCT
cuesj-252	28	6	access	access	NOUN
cuesj-252	28	7	article	article	NOUN
cuesj-252	28	8	distributed	distribute	VERB
cuesj-252	28	9	under	under	ADP
cuesj-252	28	10	the	the	DET
cuesj-252	28	11	creative	creative	ADJ
cuesj-252	28	12	commons	common	NOUN
cuesj-252	28	13	attribution	attribution	NOUN
cuesj-252	28	14	license	license	NOUN
cuesj-252	28	15	cihan	cihan	VERB
cuesj-252	28	16	university	university	NOUN
cuesj-252	28	17	-	-	PUNCT
cuesj-252	28	18	erbil	erbil	PROPN
cuesj-252	28	19	scientific	scientific	ADJ
cuesj-252	28	20	journal	journal	NOUN
cuesj-252	28	21	(	(	PUNCT
cuesj-252	28	22	cuesj	cuesj	PROPN
cuesj-252	28	23	)	)	PUNCT
cuesj-252	28	24	received	receive	VERB
cuesj-252	28	25	:	:	PUNCT
cuesj-252	28	26	jul	jul	PROPN
cuesj-252	28	27	7	7	NUM
cuesj-252	28	28	,	,	PUNCT
cuesj-252	28	29	2020	2020	NUM
cuesj-252	28	30	accepted	accept	VERB
cuesj-252	28	31	:	:	PUNCT
cuesj-252	28	32	jul	jul	PROPN
cuesj-252	28	33	25	25	NUM
cuesj-252	28	34	,	,	PUNCT
cuesj-252	28	35	2020	2020	NUM
cuesj-252	28	36	published	publish	VERB
cuesj-252	28	37	:	:	PUNCT
cuesj-252	28	38	aug	aug	PROPN
cuesj-252	28	39	13	13	NUM
cuesj-252	28	40	,	,	PUNCT
cuesj-252	28	41	2020	2020	NUM
cuesj-252	28	42	mailto	mailto	NOUN
cuesj-252	28	43	:	:	PUNCT
cuesj-252	28	44	dler.kadir%40su.edu.krd?subject=	dler.kadir%40su.edu.krd?subject=	PROPN
cuesj-252	28	45	kadir	kadir	PROPN
cuesj-252	28	46	:	:	PUNCT
cuesj-252	28	47	likelihood	likelihood	NOUN
cuesj-252	28	48	approach	approach	NOUN
cuesj-252	28	49	for	for	ADP
cuesj-252	28	50	bayesian	bayesian	NOUN
cuesj-252	28	51	logistic	logistic	NOUN
cuesj-252	28	52	weighted	weight	VERB
cuesj-252	28	53	model	model	NOUN
cuesj-252	28	54	10	10	NUM
cuesj-252	28	55	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-252	28	56	cuesj	cuesj	NOUN
cuesj-252	28	57	2020	2020	NUM
cuesj-252	28	58	,	,	PUNCT
cuesj-252	28	59	4	4	NUM
cuesj-252	28	60	(	(	PUNCT
cuesj-252	28	61	2	2	NUM
cuesj-252	28	62	):	):	PUNCT
cuesj-252	28	63	9	9	NUM
cuesj-252	28	64	-	-	SYM
cuesj-252	28	65	12	12	NUM
cuesj-252	28	66	inverse	inverse	NOUN
cuesj-252	28	67	probability	probability	NOUN
cuesj-252	28	68	weighting	weighting	NOUN
cuesj-252	28	69	(	(	PUNCT
cuesj-252	28	70	ipw	ipw	PROPN
cuesj-252	28	71	)	)	PUNCT
cuesj-252	28	72	an	an	DET
cuesj-252	28	73	ipw	ipw	PROPN
cuesj-252	28	74	method	method	NOUN
cuesj-252	28	75	will	will	AUX
cuesj-252	28	76	directly	directly	ADV
cuesj-252	28	77	model	model	VERB
cuesj-252	28	78	the	the	DET
cuesj-252	28	79	missingness	missingness	NOUN
cuesj-252	28	80	instead	instead	ADV
cuesj-252	28	81	of	of	ADP
cuesj-252	28	82	modeling	model	VERB
cuesj-252	28	83	missing	miss	VERB
cuesj-252	28	84	data	datum	NOUN
cuesj-252	28	85	observations.[5	observations.[5	NUM
cuesj-252	28	86	]	]	PUNCT
cuesj-252	28	87	ipw	ipw	PROPN
cuesj-252	28	88	is	be	AUX
cuesj-252	28	89	occasionally	occasionally	ADV
cuesj-252	28	90	termed	term	VERB
cuesj-252	28	91	“	"	PUNCT
cuesj-252	28	92	inverse	inverse	ADJ
cuesj-252	28	93	propensity	propensity	NOUN
cuesj-252	28	94	weighting	weighting	NOUN
cuesj-252	28	95	.	.	PUNCT
cuesj-252	28	96	”	"	PUNCT
cuesj-252	29	1	when	when	SCONJ
cuesj-252	29	2	a	a	DET
cuesj-252	29	3	probability	probability	NOUN
cuesj-252	29	4	score	score	NOUN
cuesj-252	29	5	is	be	AUX
cuesj-252	29	6	projected	project	VERB
cuesj-252	29	7	for	for	ADP
cuesj-252	29	8	all	all	DET
cuesj-252	29	9	subjects	subject	NOUN
cuesj-252	29	10	,	,	PUNCT
cuesj-252	29	11	the	the	DET
cuesj-252	29	12	interest	interest	NOUN
cuesj-252	29	13	covariate	covariate	VERB
cuesj-252	29	14	observed	observed	ADJ
cuesj-252	29	15	values	value	NOUN
cuesj-252	29	16	are	be	AUX
cuesj-252	29	17	weighted	weight	VERB
cuesj-252	29	18	through	through	ADP
cuesj-252	29	19	the	the	DET
cuesj-252	29	20	inverse	inverse	NOUN
cuesj-252	29	21	of	of	ADP
cuesj-252	29	22	the	the	DET
cuesj-252	29	23	relevant	relevant	ADJ
cuesj-252	29	24	probability	probability	NOUN
cuesj-252	29	25	scores	score	NOUN
cuesj-252	29	26	.	.	PUNCT
cuesj-252	30	1	response	response	NOUN
cuesj-252	30	2	probability	probability	NOUN
cuesj-252	30	3	is	be	AUX
cuesj-252	30	4	able	able	ADJ
cuesj-252	30	5	to	to	PART
cuesj-252	30	6	be	be	AUX
cuesj-252	30	7	modeled	model	VERB
cuesj-252	30	8	with	with	ADP
cuesj-252	30	9	logistical	logistical	ADJ
cuesj-252	30	10	regression	regression	NOUN
cuesj-252	30	11	models	model	NOUN
cuesj-252	30	12	and	and	CCONJ
cuesj-252	30	13	uses	use	VERB
cuesj-252	30	14	the	the	DET
cuesj-252	30	15	inverse	inverse	NOUN
cuesj-252	30	16	of	of	ADP
cuesj-252	30	17	the	the	DET
cuesj-252	30	18	probability	probability	NOUN
cuesj-252	30	19	scores	score	NOUN
cuesj-252	30	20	as	as	ADP
cuesj-252	30	21	one	one	NUM
cuesj-252	30	22	of	of	ADP
cuesj-252	30	23	the	the	DET
cuesj-252	30	24	factors	factor	NOUN
cuesj-252	30	25	of	of	ADP
cuesj-252	30	26	adjustment	adjustment	NOUN
cuesj-252	30	27	.	.	PUNCT
cuesj-252	31	1	the	the	DET
cuesj-252	31	2	ipw	ipw	PROPN
cuesj-252	31	3	adjustment	adjustment	NOUN
cuesj-252	31	4	permits	permit	VERB
cuesj-252	31	5	a	a	DET
cuesj-252	31	6	greater	great	ADJ
cuesj-252	31	7	number	number	NOUN
cuesj-252	31	8	of	of	ADP
cuesj-252	31	9	variables	variable	NOUN
cuesj-252	31	10	to	to	PART
cuesj-252	31	11	be	be	AUX
cuesj-252	31	12	employed	employ	VERB
cuesj-252	31	13	for	for	ADP
cuesj-252	31	14	predicting	predict	VERB
cuesj-252	31	15	non	non	ADJ
cuesj-252	31	16	-	-	NOUN
cuesj-252	31	17	responses	response	NOUN
cuesj-252	31	18	.	.	PUNCT
cuesj-252	32	1	the	the	DET
cuesj-252	32	2	more	more	ADV
cuesj-252	32	3	appropriate	appropriate	ADJ
cuesj-252	32	4	variable	variable	ADJ
cuesj-252	32	5	set	set	NOUN
cuesj-252	32	6	needs	need	VERB
cuesj-252	32	7	to	to	PART
cuesj-252	32	8	be	be	AUX
cuesj-252	32	9	used	use	VERB
cuesj-252	32	10	to	to	PART
cuesj-252	32	11	discover	discover	VERB
cuesj-252	32	12	the	the	DET
cuesj-252	32	13	model	model	NOUN
cuesj-252	32	14	,	,	PUNCT
cuesj-252	32	15	which	which	PRON
cuesj-252	32	16	is	be	AUX
cuesj-252	32	17	the	the	DET
cuesj-252	32	18	best	good	ADJ
cuesj-252	32	19	fit	fit	ADJ
cuesj-252	32	20	for	for	ADP
cuesj-252	32	21	predicting	predict	VERB
cuesj-252	32	22	non	non	ADJ
cuesj-252	32	23	-	-	NOUN
cuesj-252	32	24	response	response	NOUN
cuesj-252	32	25	.	.	PUNCT
cuesj-252	33	1	this	this	DET
cuesj-252	33	2	results	result	VERB
cuesj-252	33	3	in	in	ADP
cuesj-252	33	4	a	a	DET
cuesj-252	33	5	“	"	PUNCT
cuesj-252	33	6	smooth	smooth	ADJ
cuesj-252	33	7	”	"	PUNCT
cuesj-252	33	8	adjustment	adjustment	NOUN
cuesj-252	33	9	factor	factor	NOUN
cuesj-252	33	10	distribution	distribution	NOUN
cuesj-252	33	11	,	,	PUNCT
cuesj-252	33	12	with	with	ADP
cuesj-252	33	13	no	no	DET
cuesj-252	33	14	need	need	NOUN
cuesj-252	33	15	for	for	ADP
cuesj-252	33	16	choosing	choose	VERB
cuesj-252	33	17	an	an	DET
cuesj-252	33	18	arbitrary	arbitrary	ADJ
cuesj-252	33	19	cut	cut	NOUN
cuesj-252	33	20	-	-	PUNCT
cuesj-252	33	21	point.[6	point.[6	NUM
cuesj-252	33	22	]	]	PUNCT
cuesj-252	33	23	yet	yet	CCONJ
cuesj-252	33	24	,	,	PUNCT
cuesj-252	33	25	the	the	DET
cuesj-252	33	26	ipw	ipw	PROPN
cuesj-252	33	27	may	may	AUX
cuesj-252	33	28	possess	possess	VERB
cuesj-252	33	29	an	an	DET
cuesj-252	33	30	extreme	extreme	ADJ
cuesj-252	33	31	value	value	NOUN
cuesj-252	33	32	,	,	PUNCT
cuesj-252	33	33	causing	cause	VERB
cuesj-252	33	34	an	an	DET
cuesj-252	33	35	adjustment	adjustment	NOUN
cuesj-252	33	36	factor	factor	NOUN
cuesj-252	33	37	which	which	PRON
cuesj-252	33	38	might	might	AUX
cuesj-252	33	39	possess	possess	VERB
cuesj-252	33	40	a	a	DET
cuesj-252	33	41	highly	highly	ADV
cuesj-252	33	42	covariate	covariate	ADJ
cuesj-252	33	43	weight	weight	NOUN
cuesj-252	33	44	,	,	PUNCT
cuesj-252	33	45	and	and	CCONJ
cuesj-252	33	46	thus	thus	ADV
cuesj-252	33	47	,	,	PUNCT
cuesj-252	33	48	a	a	DET
cuesj-252	33	49	high	high	ADJ
cuesj-252	33	50	covariate	covariate	ADJ
cuesj-252	33	51	weight	weight	NOUN
cuesj-252	33	52	-	-	PUNCT
cuesj-252	33	53	adjusted	adjust	VERB
cuesj-252	33	54	estimates	estimate	NOUN
cuesj-252	33	55	.	.	PUNCT
cuesj-252	34	1	this	this	DET
cuesj-252	34	2	issue	issue	NOUN
cuesj-252	34	3	can	can	AUX
cuesj-252	34	4	be	be	AUX
cuesj-252	34	5	resolved	resolve	VERB
cuesj-252	34	6	by	by	ADP
cuesj-252	34	7	trimming	trim	VERB
cuesj-252	34	8	the	the	DET
cuesj-252	34	9	adjustment	adjustment	NOUN
cuesj-252	34	10	factor	factor	NOUN
cuesj-252	34	11	or	or	CCONJ
cuesj-252	34	12	trimming	trim	VERB
cuesj-252	34	13	nonresponse	nonresponse	NOUN
cuesj-252	34	14	adjusted	adjust	VERB
cuesj-252	34	15	weights	weight	NOUN
cuesj-252	34	16	.	.	PUNCT
cuesj-252	35	1	however	however	ADV
cuesj-252	35	2	,	,	PUNCT
cuesj-252	35	3	such	such	ADJ
cuesj-252	35	4	remedies	remedy	NOUN
cuesj-252	35	5	might	might	AUX
cuesj-252	35	6	increase	increase	VERB
cuesj-252	35	7	bias	bias	NOUN
cuesj-252	35	8	possibilities	possibility	NOUN
cuesj-252	35	9	.	.	PUNCT
cuesj-252	36	1	weighted	weight	VERB
cuesj-252	36	2	posterior	posterior	ADJ
cuesj-252	36	3	distributions	distribution	NOUN
cuesj-252	36	4	from	from	ADP
cuesj-252	36	5	a	a	DET
cuesj-252	36	6	bayesian	bayesian	NOUN
cuesj-252	36	7	perspective	perspective	NOUN
cuesj-252	36	8	,	,	PUNCT
cuesj-252	36	9	we	we	PRON
cuesj-252	36	10	can	can	AUX
cuesj-252	36	11	gather	gather	VERB
cuesj-252	36	12	the	the	DET
cuesj-252	36	13	posterior	posterior	ADJ
cuesj-252	36	14	distribution	distribution	NOUN
cuesj-252	36	15	π(|x	π(|x	NOUN
cuesj-252	36	16	)	)	PUNCT
cuesj-252	36	17	through	through	ADP
cuesj-252	36	18	the	the	DET
cuesj-252	36	19	combination	combination	NOUN
cuesj-252	36	20	of	of	ADP
cuesj-252	36	21	two	two	NUM
cuesj-252	36	22	types	type	NOUN
cuesj-252	36	23	of	of	ADP
cuesj-252	36	24	information	information	NOUN
cuesj-252	36	25	concerning	concern	VERB
cuesj-252	36	26	the	the	DET
cuesj-252	36	27	random	random	ADJ
cuesj-252	36	28	variable	variable	NOUN
cuesj-252	36	29	.	.	PROPN
cuesj-252	36	30	one	one	NUM
cuesj-252	36	31	source	source	NOUN
cuesj-252	36	32	is	be	AUX
cuesj-252	36	33	given	give	VERB
cuesj-252	36	34	by	by	ADP
cuesj-252	36	35	the	the	DET
cuesj-252	36	36	observed	observe	VERB
cuesj-252	36	37	data	datum	NOUN
cuesj-252	36	38	which	which	PRON
cuesj-252	36	39	are	be	AUX
cuesj-252	36	40	summarized	summarize	VERB
cuesj-252	36	41	by	by	ADP
cuesj-252	36	42	the	the	DET
cuesj-252	36	43	likelihood	likelihood	NOUN
cuesj-252	36	44	function	function	NOUN
cuesj-252	36	45	,	,	PUNCT
cuesj-252	36	46	and	and	CCONJ
cuesj-252	36	47	the	the	DET
cuesj-252	36	48	other	other	ADJ
cuesj-252	36	49	information	information	NOUN
cuesj-252	36	50	source	source	NOUN
cuesj-252	36	51	is	be	AUX
cuesj-252	36	52	the	the	DET
cuesj-252	36	53	previous	previous	ADJ
cuesj-252	36	54	information	information	NOUN
cuesj-252	36	55	regarding	regard	VERB
cuesj-252	36	56	its	its	PRON
cuesj-252	36	57	distribution	distribution	NOUN
cuesj-252	36	58	π(	π(	NOUN
cuesj-252	36	59	)	)	PUNCT
cuesj-252	36	60	.	.	PUNCT
cuesj-252	37	1	weighted	weight	VERB
cuesj-252	37	2	posterior	posterior	ADJ
cuesj-252	37	3	distributions	distribution	NOUN
cuesj-252	37	4	can	can	AUX
cuesj-252	37	5	be	be	AUX
cuesj-252	37	6	defined	define	VERB
cuesj-252	37	7	through	through	ADP
cuesj-252	37	8	the	the	DET
cuesj-252	37	9	replacement	replacement	NOUN
cuesj-252	37	10	of	of	ADP
cuesj-252	37	11	the	the	DET
cuesj-252	37	12	likelihood	likelihood	NOUN
cuesj-252	37	13	function	function	NOUN
cuesj-252	37	14	by	by	ADP
cuesj-252	37	15	its	its	PRON
cuesj-252	37	16	ipw	ipw	PROPN
cuesj-252	37	17	counterpart	counterpart	NOUN
cuesj-252	37	18	,	,	PUNCT
cuesj-252	37	19	as	as	SCONJ
cuesj-252	37	20	discussed	discuss	VERB
cuesj-252	37	21	in	in	ADP
cuesj-252	37	22	the	the	DET
cuesj-252	37	23	previous	previous	ADJ
cuesj-252	37	24	section	section	NOUN
cuesj-252	37	25	.	.	PUNCT
cuesj-252	38	1	the	the	DET
cuesj-252	38	2	weighted	weighted	ADJ
cuesj-252	38	3	posterior	posterior	ADJ
cuesj-252	38	4	distribution	distribution	NOUN
cuesj-252	38	5	is	be	AUX
cuesj-252	38	6	as	as	SCONJ
cuesj-252	38	7	follows	follow	VERB
cuesj-252	38	8	:	:	PUNCT
cuesj-252	38	9	�	�	PROPN
cuesj-252	38	10	�	�	PROPN
cuesj-252	38	11	�	�	PROPN
cuesj-252	38	12	�	�	PROPN
cuesj-252	38	13	�	�	PROPN
cuesj-252	38	14	ipw	ipw	PROPN
cuesj-252	38	15	ipwx	ipwx	PROPN
cuesj-252	38	16	l	l	PROPN
cuesj-252	38	17	x|	x|	PROPN
cuesj-252	38	18	|	|	PROPN
cuesj-252	38	19	�	�	PROPN
cuesj-252	38	20	�	�	PROPN
cuesj-252	38	21	�	�	PROPN
cuesj-252	38	22	�	�	PROPN
cuesj-252	38	23	�	�	PROPN
cuesj-252	38	24	�	�	PROPN
cuesj-252	38	25	�	�	PROPN
cuesj-252	38	26	�	�	PROPN
cuesj-252	38	27	�	�	PROPN
cuesj-252	38	28	(	(	PUNCT
cuesj-252	38	29	1	1	NUM
cuesj-252	38	30	)	)	PUNCT
cuesj-252	38	31	next	next	ADV
cuesj-252	38	32	,	,	PUNCT
cuesj-252	38	33	we	we	PRON
cuesj-252	38	34	propose	propose	VERB
cuesj-252	38	35	ipws	ipws	NOUN
cuesj-252	38	36	evaluated	evaluate	VERB
cuesj-252	38	37	as	as	ADP
cuesj-252	38	38	in	in	ADP
cuesj-252	38	39	the	the	DET
cuesj-252	38	40	above	above	ADJ
cuesj-252	38	41	equation	equation	NOUN
cuesj-252	38	42	of	of	ADP
cuesj-252	38	43	the	the	DET
cuesj-252	38	44	form	form	NOUN
cuesj-252	38	45	ˆ	ˆ	ADP
cuesj-252	38	46	ˆipw	ˆipw	NOUN
cuesj-252	38	47	(	(	PUNCT
cuesj-252	38	48	)	)	PUNCT
cuesj-252	38	49	pw	pw	PROPN
cuesj-252	38	50	(	(	PUNCT
cuesj-252	38	51	;	;	PUNCT
cuesj-252	38	52	,	,	PUNCT
cuesj-252	38	53	)	)	PUNCT
cuesj-252	38	54	θ	θ	X
cuesj-252	39	1	=	=	NOUN
cuesj-252	39	2	i	i	PRON
cuesj-252	39	3	i	i	PRON
cuesj-252	39	4	ipw	ipw	VERB
cuesj-252	39	5	nx	nx	PROPN
cuesj-252	39	6	x	x	PROPN
cuesj-252	39	7	f	f	PROPN
cuesj-252	39	8	.	.	PUNCT
cuesj-252	40	1	it	it	PRON
cuesj-252	40	2	is	be	AUX
cuesj-252	40	3	apparent	apparent	ADJ
cuesj-252	40	4	that	that	SCONJ
cuesj-252	40	5	from	from	ADP
cuesj-252	40	6	the	the	DET
cuesj-252	40	7	part	part	NOUN
cuesj-252	40	8	of	of	ADP
cuesj-252	40	9	lipw	lipw	PROPN
cuesj-252	40	10	(	(	PUNCT
cuesj-252	40	11	x|	x|	NOUN
cuesj-252	40	12	)	)	PUNCT
cuesj-252	40	13	,	,	PUNCT
cuesj-252	40	14	we	we	PRON
cuesj-252	40	15	can	can	AUX
cuesj-252	40	16	obtain	obtain	VERB
cuesj-252	40	17	first	first	ADJ
cuesj-252	40	18	-	-	PUNCT
cuesj-252	40	19	order	order	NOUN
cuesj-252	40	20	property	property	NOUN
cuesj-252	40	21	of	of	ADP
cuesj-252	40	22	the	the	DET
cuesj-252	40	23	actual	actual	ADJ
cuesj-252	40	24	function	function	NOUN
cuesj-252	40	25	likelihood	likelihood	NOUN
cuesj-252	40	26	under	under	ADP
cuesj-252	40	27	the	the	DET
cuesj-252	40	28	model	model	NOUN
cuesj-252	40	29	assumption	assumption	NOUN
cuesj-252	40	30	;	;	PUNCT
cuesj-252	40	31	therefore	therefore	ADV
cuesj-252	40	32	,	,	PUNCT
cuesj-252	40	33	this	this	PRON
cuesj-252	40	34	has	have	VERB
cuesj-252	40	35	validity	validity	NOUN
cuesj-252	40	36	for	for	ADP
cuesj-252	40	37	bayesian	bayesian	NOUN
cuesj-252	40	38	estimates	estimate	NOUN
cuesj-252	40	39	in	in	ADP
cuesj-252	40	40	a	a	DET
cuesj-252	40	41	standard	standard	ADJ
cuesj-252	40	42	manner	manner	NOUN
cuesj-252	40	43	.	.	PUNCT
cuesj-252	41	1	one	one	NUM
cuesj-252	41	2	benefit	benefit	NOUN
cuesj-252	41	3	of	of	ADP
cuesj-252	41	4	weighting	weighting	NOUN
cuesj-252	41	5	is	be	AUX
cuesj-252	41	6	that	that	SCONJ
cuesj-252	41	7	it	it	PRON
cuesj-252	41	8	uses	use	VERB
cuesj-252	41	9	other	other	ADJ
cuesj-252	41	10	pseudolikelihood	pseudolikelihood	NOUN
cuesj-252	41	11	functions	function	NOUN
cuesj-252	41	12	,	,	PUNCT
cuesj-252	41	13	leading	lead	VERB
cuesj-252	41	14	to	to	ADP
cuesj-252	41	15	posterior	posterior	ADJ
cuesj-252	41	16	distributions	distribution	NOUN
cuesj-252	41	17	which	which	PRON
cuesj-252	41	18	belong	belong	VERB
cuesj-252	41	19	to	to	ADP
cuesj-252	41	20	the	the	DET
cuesj-252	41	21	same	same	ADJ
cuesj-252	41	22	family	family	NOUN
cuesj-252	41	23	of	of	ADP
cuesj-252	41	24	those	those	PRON
cuesj-252	41	25	obtained	obtain	VERB
cuesj-252	41	26	through	through	ADP
cuesj-252	41	27	the	the	DET
cuesj-252	41	28	use	use	NOUN
cuesj-252	41	29	of	of	ADP
cuesj-252	41	30	the	the	DET
cuesj-252	41	31	genuine	genuine	ADJ
cuesj-252	41	32	likelihood	likelihood	NOUN
cuesj-252	41	33	function	function	NOUN
cuesj-252	41	34	.	.	PUNCT
cuesj-252	42	1	therefore	therefore	ADV
cuesj-252	42	2	,	,	PUNCT
cuesj-252	42	3	the	the	DET
cuesj-252	42	4	weighted	weight	VERB
cuesj-252	42	5	posterior	posterior	ADJ
cuesj-252	42	6	distributions	distribution	NOUN
cuesj-252	42	7	vary	vary	VERB
cuesj-252	42	8	from	from	ADP
cuesj-252	42	9	the	the	DET
cuesj-252	42	10	genuine	genuine	ADJ
cuesj-252	42	11	posterior	posterior	ADJ
cuesj-252	42	12	distributions	distribution	NOUN
cuesj-252	42	13	for	for	ADP
cuesj-252	42	14	the	the	DET
cuesj-252	42	15	estimated	estimate	VERB
cuesj-252	42	16	values	value	NOUN
cuesj-252	42	17	.	.	PUNCT
cuesj-252	43	1	it	it	PRON
cuesj-252	43	2	can	can	AUX
cuesj-252	43	3	seem	seem	VERB
cuesj-252	43	4	that	that	SCONJ
cuesj-252	43	5	there	there	PRON
cuesj-252	43	6	is	be	VERB
cuesj-252	43	7	a	a	DET
cuesj-252	43	8	conflict	conflict	NOUN
cuesj-252	43	9	between	between	ADP
cuesj-252	43	10	the	the	DET
cuesj-252	43	11	method	method	NOUN
cuesj-252	43	12	and	and	CCONJ
cuesj-252	43	13	a	a	DET
cuesj-252	43	14	proper	proper	ADJ
cuesj-252	43	15	bayesian	bayesian	NOUN
cuesj-252	43	16	perspective	perspective	NOUN
cuesj-252	43	17	.	.	PUNCT
cuesj-252	44	1	this	this	PRON
cuesj-252	44	2	is	be	AUX
cuesj-252	44	3	because	because	SCONJ
cuesj-252	44	4	the	the	DET
cuesj-252	44	5	weighted	weight	VERB
cuesj-252	44	6	likelihood	likelihood	NOUN
cuesj-252	44	7	function	function	NOUN
cuesj-252	44	8	is	be	AUX
cuesj-252	44	9	not	not	PART
cuesj-252	44	10	immediately	immediately	ADV
cuesj-252	44	11	driven	drive	VERB
cuesj-252	44	12	by	by	ADP
cuesj-252	44	13	a	a	DET
cuesj-252	44	14	probabilistic	probabilistic	ADJ
cuesj-252	44	15	model	model	NOUN
cuesj-252	44	16	;	;	PUNCT
cuesj-252	44	17	rather	rather	ADV
cuesj-252	44	18	,	,	PUNCT
cuesj-252	44	19	it	it	PRON
cuesj-252	44	20	is	be	AUX
cuesj-252	44	21	driven	drive	VERB
cuesj-252	44	22	by	by	ADP
cuesj-252	44	23	adaptive	adaptive	ADJ
cuesj-252	44	24	weights	weight	NOUN
cuesj-252	44	25	.	.	PUNCT
cuesj-252	45	1	the	the	DET
cuesj-252	45	2	data	datum	NOUN
cuesj-252	45	3	still	still	ADV
cuesj-252	45	4	tell	tell	VERB
cuesj-252	45	5	a	a	DET
cuesj-252	45	6	story	story	NOUN
cuesj-252	45	7	;	;	PUNCT
cuesj-252	45	8	however	however	ADV
cuesj-252	45	9	,	,	PUNCT
cuesj-252	45	10	some	some	DET
cuesj-252	45	11	values	value	NOUN
cuesj-252	45	12	are	be	AUX
cuesj-252	45	13	not	not	PART
cuesj-252	45	14	consistent	consistent	ADJ
cuesj-252	45	15	with	with	ADP
cuesj-252	45	16	the	the	DET
cuesj-252	45	17	required	require	VERB
cuesj-252	45	18	models	model	NOUN
cuesj-252	45	19	,	,	PUNCT
cuesj-252	45	20	and	and	CCONJ
cuesj-252	45	21	we	we	PRON
cuesj-252	45	22	are	be	AUX
cuesj-252	45	23	unable	unable	ADJ
cuesj-252	45	24	to	to	PART
cuesj-252	45	25	simply	simply	ADV
cuesj-252	45	26	delete	delete	VERB
cuesj-252	45	27	outliers	outlier	NOUN
cuesj-252	45	28	,	,	PUNCT
cuesj-252	45	29	yet	yet	CCONJ
cuesj-252	45	30	it	it	PRON
cuesj-252	45	31	still	still	ADV
cuesj-252	45	32	contributes	contribute	VERB
cuesj-252	45	33	to	to	ADP
cuesj-252	45	34	the	the	DET
cuesj-252	45	35	posterior	posterior	NOUN
cuesj-252	45	36	estimate.[7	estimate.[7	X
cuesj-252	45	37	]	]	PUNCT
cuesj-252	45	38	preterm	preterm	NOUN
cuesj-252	45	39	data	datum	NOUN
cuesj-252	45	40	for	for	ADP
cuesj-252	45	41	using	use	VERB
cuesj-252	45	42	logistic	logistic	ADJ
cuesj-252	45	43	regression	regression	NOUN
cuesj-252	45	44	the	the	DET
cuesj-252	45	45	data	datum	NOUN
cuesj-252	45	46	were	be	AUX
cuesj-252	45	47	collected	collect	VERB
cuesj-252	45	48	from	from	ADP
cuesj-252	45	49	the	the	DET
cuesj-252	45	50	neonatal	neonatal	ADJ
cuesj-252	45	51	intensive	intensive	ADJ
cuesj-252	45	52	care	care	NOUN
cuesj-252	45	53	unit	unit	NOUN
cuesj-252	45	54	at	at	ADP
cuesj-252	45	55	erbil	erbil	PROPN
cuesj-252	45	56	maternity	maternity	PROPN
cuesj-252	45	57	hospital	hospital	NOUN
cuesj-252	45	58	from	from	ADP
cuesj-252	45	59	2012	2012	NUM
cuesj-252	45	60	to	to	ADP
cuesj-252	45	61	2017	2017	NUM
cuesj-252	45	62	.	.	PUNCT
cuesj-252	46	1	in	in	ADP
cuesj-252	46	2	total	total	ADJ
cuesj-252	46	3	,	,	PUNCT
cuesj-252	46	4	570	570	NUM
cuesj-252	46	5	babies	baby	NOUN
cuesj-252	46	6	(	(	PUNCT
cuesj-252	46	7	288	288	NUM
cuesj-252	46	8	males	male	NOUN
cuesj-252	46	9	and	and	CCONJ
cuesj-252	46	10	282	282	NUM
cuesj-252	46	11	females	female	NOUN
cuesj-252	46	12	)	)	PUNCT
cuesj-252	46	13	were	be	AUX
cuesj-252	46	14	born	bear	VERB
cuesj-252	46	15	very	very	ADV
cuesj-252	46	16	preterm	preterm	ADJ
cuesj-252	46	17	.	.	PUNCT
cuesj-252	47	1	we	we	PRON
cuesj-252	47	2	have	have	AUX
cuesj-252	47	3	considered	consider	VERB
cuesj-252	47	4	the	the	DET
cuesj-252	47	5	infants	infant	NOUN
cuesj-252	47	6	born	bear	VERB
cuesj-252	47	7	before	before	ADP
cuesj-252	47	8	28	28	NUM
cuesj-252	47	9	weeks	week	NOUN
cuesj-252	47	10	.	.	PUNCT
cuesj-252	48	1	the	the	DET
cuesj-252	48	2	mental	mental	PROPN
cuesj-252	48	3	development	development	PROPN
cuesj-252	48	4	index	index	NOUN
cuesj-252	48	5	approach	approach	NOUN
cuesj-252	48	6	was	be	AUX
cuesj-252	48	7	used	use	VERB
cuesj-252	48	8	for	for	ADP
cuesj-252	48	9	assessing	assess	VERB
cuesj-252	48	10	the	the	DET
cuesj-252	48	11	cognitive	cognitive	ADJ
cuesj-252	48	12	development	development	NOUN
cuesj-252	48	13	of	of	ADP
cuesj-252	48	14	those	those	PRON
cuesj-252	48	15	born	bear	VERB
cuesj-252	48	16	very	very	ADV
cuesj-252	48	17	preterm	preterm	ADJ
cuesj-252	48	18	.	.	PUNCT
cuesj-252	49	1	almost	almost	ADV
cuesj-252	49	2	half	half	NOUN
cuesj-252	49	3	of	of	ADP
cuesj-252	49	4	the	the	DET
cuesj-252	49	5	information	information	NOUN
cuesj-252	49	6	for	for	ADP
cuesj-252	49	7	the	the	DET
cuesj-252	49	8	babies	baby	NOUN
cuesj-252	49	9	was	be	AUX
cuesj-252	49	10	missing	miss	VERB
cuesj-252	49	11	,	,	PUNCT
cuesj-252	49	12	meaning	mean	VERB
cuesj-252	49	13	that	that	SCONJ
cuesj-252	49	14	we	we	PRON
cuesj-252	49	15	do	do	AUX
cuesj-252	49	16	not	not	PART
cuesj-252	49	17	know	know	VERB
cuesj-252	49	18	whether	whether	SCONJ
cuesj-252	49	19	they	they	PRON
cuesj-252	49	20	have	have	VERB
cuesj-252	49	21	cognitive	cognitive	ADJ
cuesj-252	49	22	development	development	NOUN
cuesj-252	49	23	issues	issue	NOUN
cuesj-252	49	24	.	.	PUNCT
cuesj-252	50	1	now	now	ADV
cuesj-252	50	2	let	let	VERB
cuesj-252	50	3	i1	i1	PROPN
cuesj-252	50	4	p	p	NOUN
cuesj-252	50	5	0	0	NUM
cuesj-252	50	6			NOUN
cuesj-252	50	7	=	=	NOUN
cuesj-252	50	8			PRON
cuesj-252	50	9			NOUN
cuesj-252	50	10	i	i	PRON
cuesj-252	50	11	if	if	SCONJ
cuesj-252	50	12	thedata	thedata	ADJ
cuesj-252	50	13	was	be	AUX
cuesj-252	50	14	collelected	collelecte	VERB
cuesj-252	50	15	with	with	ADP
cuesj-252	50	16	probability	probability	NOUN
cuesj-252	50	17	r	r	NOUN
cuesj-252	50	18	if	if	SCONJ
cuesj-252	50	19	thethereis	thethereis	INTJ
cuesj-252	50	20	no	no	DET
cuesj-252	50	21	response	response	NOUN
cuesj-252	50	22	(	(	PUNCT
cuesj-252	50	23	2	2	NUM
cuesj-252	50	24	)	)	PUNCT
cuesj-252	50	25	•	•	NOUN
cuesj-252	50	26	the	the	DET
cuesj-252	50	27	procedure	procedure	NOUN
cuesj-252	50	28	,	,	PUNCT
cuesj-252	50	29	therefore	therefore	ADV
cuesj-252	50	30	,	,	PUNCT
cuesj-252	50	31	involves	involve	VERB
cuesj-252	50	32	:	:	PUNCT
cuesj-252	50	33	fitting	fit	VERB
cuesj-252	50	34	a	a	DET
cuesj-252	50	35	binary	binary	ADJ
cuesj-252	50	36	logistic	logistic	ADJ
cuesj-252	50	37	regression	regression	NOUN
cuesj-252	50	38	,	,	PUNCT
cuesj-252	50	39	responding	respond	VERB
cuesj-252	50	40	to	to	ADP
cuesj-252	50	41	the	the	DET
cuesj-252	50	42	research	research	NOUN
cuesj-252	50	43	under	under	ADP
cuesj-252	50	44	observation	observation	NOUN
cuesj-252	50	45	(	(	PUNCT
cuesj-252	50	46	1	1	NUM
cuesj-252	50	47	if	if	SCONJ
cuesj-252	50	48	observed	observe	VERB
cuesj-252	50	49	,	,	PUNCT
cuesj-252	50	50	0	0	PUNCT
cuesj-252	50	51	if	if	SCONJ
cuesj-252	50	52	not	not	PART
cuesj-252	50	53	)	)	PUNCT
cuesj-252	50	54	with	with	ADP
cuesj-252	50	55	the	the	DET
cuesj-252	50	56	more	more	ADV
cuesj-252	50	57	appropriate	appropriate	ADJ
cuesj-252	50	58	variable	variable	NOUN
cuesj-252	50	59	set	set	VERB
cuesj-252	50	60	as	as	ADP
cuesj-252	50	61	an	an	DET
cuesj-252	50	62	explanatory	explanatory	ADJ
cuesj-252	50	63	variable	variable	NOUN
cuesj-252	50	64	.	.	PUNCT
cuesj-252	51	1	•	•	NUM
cuesj-252	52	1	obtaining	obtain	VERB
cuesj-252	52	2	the	the	DET
cuesj-252	52	3	fitted	fit	VERB
cuesj-252	52	4	probability	probability	NOUN
cuesj-252	52	5	for	for	ADP
cuesj-252	52	6	all	all	DET
cuesj-252	52	7	infants	infant	NOUN
cuesj-252	52	8	,	,	PUNCT
cuesj-252	52	9	pi	pi	NOUN
cuesj-252	52	10	,	,	PUNCT
cuesj-252	52	11	i	i	PRON
cuesj-252	52	12	∈(1,	∈(1,	VERB
cuesj-252	52	13	…	…	PUNCT
cuesj-252	52	14	,n	,n	NOUN
cuesj-252	52	15	)	)	PUNCT
cuesj-252	52	16	•	•	NUM
cuesj-252	52	17	calculation	calculation	NOUN
cuesj-252	52	18	of	of	ADP
cuesj-252	52	19	the	the	DET
cuesj-252	52	20	ipw	ipw	PROPN
cuesj-252	52	21	for	for	ADP
cuesj-252	52	22	all	all	DET
cuesj-252	52	23	infants	infant	NOUN
cuesj-252	52	24	ipwi	ipwi	NOUN
cuesj-252	52	25	=	=	SYM
cuesj-252	52	26	1	1	NUM
cuesj-252	52	27	/	/	SYM
cuesj-252	52	28	pi	pi	NOUN
cuesj-252	52	29	)	)	PUNCT
cuesj-252	52	30	and	and	CCONJ
cuesj-252	52	31	uses	use	VERB
cuesj-252	52	32	ipw	ipw	PROPN
cuesj-252	52	33	to	to	PART
cuesj-252	52	34	fit	fit	VERB
cuesj-252	52	35	weighted	weight	VERB
cuesj-252	52	36	bayesian	bayesian	NOUN
cuesj-252	52	37	logistic	logistic	ADJ
cuesj-252	52	38	regression	regression	NOUN
cuesj-252	52	39	models	model	NOUN
cuesj-252	52	40	using	use	VERB
cuesj-252	52	41	winbugs	winbug	NOUN
cuesj-252	52	42	software	software	NOUN
cuesj-252	52	43	.	.	PUNCT
cuesj-252	53	1	through	through	ADP
cuesj-252	53	2	the	the	DET
cuesj-252	53	3	assumption	assumption	NOUN
cuesj-252	53	4	that	that	SCONJ
cuesj-252	53	5	the	the	DET
cuesj-252	53	6	posterior	posterior	ADJ
cuesj-252	53	7	weighting	weighting	NOUN
cuesj-252	53	8	model	model	NOUN
cuesj-252	53	9	is	be	AUX
cuesj-252	53	10	correct	correct	ADJ
cuesj-252	53	11	,	,	PUNCT
cuesj-252	53	12	we	we	PRON
cuesj-252	53	13	can	can	AUX
cuesj-252	53	14	obtain	obtain	VERB
cuesj-252	53	15	consistent	consistent	ADJ
cuesj-252	53	16	parameter	parameter	NOUN
cuesj-252	53	17	estimates	estimate	NOUN
cuesj-252	53	18	to	to	PART
cuesj-252	53	19	know	know	VERB
cuesj-252	53	20	the	the	DET
cuesj-252	53	21	effect	effect	NOUN
cuesj-252	53	22	of	of	ADP
cuesj-252	53	23	the	the	DET
cuesj-252	53	24	outcome	outcome	NOUN
cuesj-252	53	25	model	model	NOUN
cuesj-252	53	26	.	.	PUNCT
cuesj-252	54	1	yet	yet	ADV
cuesj-252	54	2	,	,	PUNCT
cuesj-252	54	3	the	the	DET
cuesj-252	54	4	major	major	ADJ
cuesj-252	54	5	issue	issue	NOUN
cuesj-252	54	6	in	in	ADP
cuesj-252	54	7	weighted	weighted	ADJ
cuesj-252	54	8	data	datum	NOUN
cuesj-252	54	9	analysis	analysis	NOUN
cuesj-252	54	10	is	be	AUX
cuesj-252	54	11	that	that	SCONJ
cuesj-252	54	12	the	the	DET
cuesj-252	54	13	weight	weight	NOUN
cuesj-252	54	14	is	be	AUX
cuesj-252	54	15	not	not	PART
cuesj-252	54	16	representative	representative	NOUN
cuesj-252	54	17	of	of	ADP
cuesj-252	54	18	the	the	DET
cuesj-252	54	19	actual	actual	ADJ
cuesj-252	54	20	subject	subject	ADJ
cuesj-252	54	21	number	number	NOUN
cuesj-252	54	22	;	;	PUNCT
cuesj-252	54	23	however	however	ADV
cuesj-252	54	24	,	,	PUNCT
cuesj-252	54	25	only	only	ADV
cuesj-252	54	26	an	an	DET
cuesj-252	54	27	expected	expect	VERB
cuesj-252	54	28	number	number	NOUN
cuesj-252	54	29	might	might	AUX
cuesj-252	54	30	be	be	AUX
cuesj-252	54	31	applicable	applicable	ADJ
cuesj-252	54	32	if	if	SCONJ
cuesj-252	54	33	the	the	DET
cuesj-252	54	34	statistical	statistical	ADJ
cuesj-252	54	35	weight	weight	NOUN
cuesj-252	54	36	features	feature	VERB
cuesj-252	54	37	every	every	DET
cuesj-252	54	38	detail	detail	NOUN
cuesj-252	54	39	regarding	regard	VERB
cuesj-252	54	40	the	the	DET
cuesj-252	54	41	sampling	sample	VERB
cuesj-252	54	42	probability	probability	NOUN
cuesj-252	54	43	.	.	PUNCT
cuesj-252	55	1	identical	identical	ADJ
cuesj-252	55	2	samples	sample	NOUN
cuesj-252	55	3	appear	appear	VERB
cuesj-252	55	4	from	from	ADP
cuesj-252	55	5	simple	simple	ADJ
cuesj-252	55	6	random	random	ADJ
cuesj-252	55	7	sampling	sampling	NOUN
cuesj-252	55	8	(	(	PUNCT
cuesj-252	55	9	whereby	whereby	SCONJ
cuesj-252	55	10	every	every	DET
cuesj-252	55	11	individual	individual	NOUN
cuesj-252	55	12	of	of	ADP
cuesj-252	55	13	the	the	DET
cuesj-252	55	14	same	same	ADJ
cuesj-252	55	15	sizes	size	NOUN
cuesj-252	55	16	is	be	AUX
cuesj-252	55	17	able	able	ADJ
cuesj-252	55	18	to	to	PART
cuesj-252	55	19	be	be	AUX
cuesj-252	55	20	sampled	sample	VERB
cuesj-252	55	21	with	with	ADP
cuesj-252	55	22	an	an	DET
cuesj-252	55	23	equal	equal	ADJ
cuesj-252	55	24	probability).[4	probability).[4	NOUN
cuesj-252	55	25	]	]	X
cuesj-252	55	26	an	an	DET
cuesj-252	55	27	additional	additional	ADJ
cuesj-252	55	28	issue	issue	NOUN
cuesj-252	55	29	with	with	ADP
cuesj-252	55	30	using	use	VERB
cuesj-252	55	31	ipw	ipw	PROPN
cuesj-252	55	32	is	be	AUX
cuesj-252	55	33	where	where	SCONJ
cuesj-252	55	34	a	a	DET
cuesj-252	55	35	missingness	missingness	ADJ
cuesj-252	55	36	predictor	predictor	NOUN
cuesj-252	55	37	distribution	distribution	NOUN
cuesj-252	55	38	in	in	ADP
cuesj-252	55	39	full	full	ADJ
cuesj-252	55	40	cases	case	NOUN
cuesj-252	55	41	varies	vary	VERB
cuesj-252	55	42	from	from	ADP
cuesj-252	55	43	incomplete	incomplete	ADJ
cuesj-252	55	44	cases	case	NOUN
cuesj-252	55	45	.	.	PUNCT
cuesj-252	56	1	the	the	DET
cuesj-252	56	2	ipw	ipw	PROPN
cuesj-252	56	3	will	will	AUX
cuesj-252	56	4	then	then	ADV
cuesj-252	56	5	greatly	greatly	ADV
cuesj-252	56	6	vary	vary	VERB
cuesj-252	56	7	since	since	SCONJ
cuesj-252	56	8	complete	complete	ADJ
cuesj-252	56	9	case	case	NOUN
cuesj-252	56	10	analyses	analysis	NOUN
cuesj-252	56	11	,	,	PUNCT
cuesj-252	56	12	where	where	SCONJ
cuesj-252	56	13	the	the	DET
cuesj-252	56	14	missingness	missingness	ADJ
cuesj-252	56	15	predictor	predictor	NOUN
cuesj-252	56	16	observation	observation	NOUN
cuesj-252	56	17	is	be	AUX
cuesj-252	56	18	nearer	near	ADJ
cuesj-252	56	19	the	the	DET
cuesj-252	56	20	center	center	NOUN
cuesj-252	56	21	of	of	ADP
cuesj-252	56	22	the	the	DET
cuesj-252	56	23	observation	observation	NOUN
cuesj-252	56	24	distributions	distribution	NOUN
cuesj-252	56	25	in	in	ADP
cuesj-252	56	26	the	the	DET
cuesj-252	56	27	incomplete	incomplete	ADJ
cuesj-252	56	28	case	case	NOUN
cuesj-252	56	29	which	which	PRON
cuesj-252	56	30	might	might	AUX
cuesj-252	56	31	obtain	obtain	VERB
cuesj-252	56	32	a	a	DET
cuesj-252	56	33	larger	large	ADJ
cuesj-252	56	34	weight	weight	NOUN
cuesj-252	56	35	.	.	PUNCT
cuesj-252	57	1	this	this	DET
cuesj-252	57	2	will	will	AUX
cuesj-252	57	3	,	,	PUNCT
cuesj-252	57	4	therefore	therefore	ADV
cuesj-252	57	5	,	,	PUNCT
cuesj-252	57	6	cause	cause	VERB
cuesj-252	57	7	a	a	DET
cuesj-252	57	8	larger	large	ADJ
cuesj-252	57	9	standard	standard	NOUN
cuesj-252	57	10	error.[8	error.[8	NOUN
cuesj-252	57	11	]	]	PUNCT
cuesj-252	57	12	when	when	SCONJ
cuesj-252	57	13	the	the	DET
cuesj-252	57	14	weight	weight	NOUN
cuesj-252	57	15	can	can	AUX
cuesj-252	57	16	account	account	VERB
cuesj-252	57	17	for	for	ADP
cuesj-252	57	18	the	the	DET
cuesj-252	57	19	missing	miss	VERB
cuesj-252	57	20	data	datum	NOUN
cuesj-252	57	21	,	,	PUNCT
cuesj-252	57	22	parameters	parameter	NOUN
cuesj-252	57	23	must	must	AUX
cuesj-252	57	24	be	be	AUX
cuesj-252	57	25	predicted	predict	VERB
cuesj-252	57	26	.	.	PUNCT
cuesj-252	58	1	the	the	DET
cuesj-252	58	2	complete	complete	ADJ
cuesj-252	58	3	case	case	NOUN
cuesj-252	58	4	data	data	NOUN
cuesj-252	58	5	variance	variance	NOUN
cuesj-252	58	6	estimator	estimator	NOUN
cuesj-252	58	7	makes	make	VERB
cuesj-252	58	8	the	the	DET
cuesj-252	58	9	assumption	assumption	NOUN
cuesj-252	58	10	that	that	SCONJ
cuesj-252	58	11	the	the	DET
cuesj-252	58	12	weight	weight	NOUN
cuesj-252	58	13	is	be	AUX
cuesj-252	58	14	known	know	VERB
cuesj-252	58	15	and	and	CCONJ
cuesj-252	58	16	ignores	ignore	VERB
cuesj-252	58	17	any	any	DET
cuesj-252	58	18	uncertainty	uncertainty	NOUN
cuesj-252	58	19	in	in	ADP
cuesj-252	58	20	estimations	estimation	NOUN
cuesj-252	58	21	about	about	ADP
cuesj-252	58	22	them.[9	them.[9	NOUN
cuesj-252	58	23	]	]	PUNCT
cuesj-252	58	24	seaman	seaman	NOUN
cuesj-252	58	25	et	et	PROPN
cuesj-252	58	26	al	al	PROPN
cuesj-252	58	27	.	.	PROPN
cuesj-252	58	28	recommend	recommend	VERB
cuesj-252	58	29	the	the	DET
cuesj-252	58	30	use	use	NOUN
cuesj-252	58	31	of	of	ADP
cuesj-252	58	32	sandwich	sandwich	NOUN
cuesj-252	58	33	estimators	estimator	NOUN
cuesj-252	58	34	in	in	ADP
cuesj-252	58	35	accounting	account	VERB
cuesj-252	58	36	for	for	ADP
cuesj-252	58	37	uncertainties	uncertainty	NOUN
cuesj-252	58	38	in	in	ADP
cuesj-252	58	39	the	the	DET
cuesj-252	58	40	weights	weight	NOUN
cuesj-252	58	41	.	.	PUNCT
cuesj-252	59	1	in	in	ADP
cuesj-252	59	2	reality	reality	NOUN
cuesj-252	59	3	,	,	PUNCT
cuesj-252	59	4	the	the	DET
cuesj-252	59	5	true	true	ADJ
cuesj-252	59	6	asymptotic	asymptotic	ADJ
cuesj-252	59	7	uncertainty	uncertainty	NOUN
cuesj-252	59	8	is	be	AUX
cuesj-252	59	9	frequently	frequently	ADV
cuesj-252	59	10	more	more	ADJ
cuesj-252	59	11	when	when	SCONJ
cuesj-252	59	12	a	a	DET
cuesj-252	59	13	true	true	ADJ
cuesj-252	59	14	weight	weight	NOUN
cuesj-252	59	15	is	be	AUX
cuesj-252	59	16	utilized	utilize	VERB
cuesj-252	59	17	than	than	ADP
cuesj-252	59	18	when	when	SCONJ
cuesj-252	59	19	they	they	PRON
cuesj-252	59	20	are	be	AUX
cuesj-252	59	21	estimated	estimate	VERB
cuesj-252	59	22	.	.	PUNCT
cuesj-252	60	1	thus	thus	ADV
cuesj-252	60	2	,	,	PUNCT
cuesj-252	60	3	ignoring	ignore	VERB
cuesj-252	60	4	uncertainties	uncertainty	NOUN
cuesj-252	60	5	in	in	ADP
cuesj-252	60	6	a	a	DET
cuesj-252	60	7	fixed	fix	VERB
cuesj-252	60	8	weight	weight	NOUN
cuesj-252	60	9	might	might	AUX
cuesj-252	60	10	cause	cause	VERB
cuesj-252	60	11	a	a	DET
cuesj-252	60	12	standard	standard	NOUN
cuesj-252	60	13	error.[8	error.[8	NOUN
cuesj-252	60	14	]	]	PUNCT
cuesj-252	60	15	here	here	ADV
cuesj-252	60	16	,	,	PUNCT
cuesj-252	60	17	the	the	DET
cuesj-252	60	18	weights	weight	NOUN
cuesj-252	60	19	value	value	NOUN
cuesj-252	60	20	was	be	AUX
cuesj-252	60	21	altered	alter	VERB
cuesj-252	60	22	in	in	ADP
cuesj-252	60	23	all	all	DET
cuesj-252	60	24	iterations	iteration	NOUN
cuesj-252	60	25	using	use	VERB
cuesj-252	60	26	markov	markov	NOUN
cuesj-252	60	27	chain	chain	NOUN
cuesj-252	60	28	monte	monte	PROPN
cuesj-252	60	29	carlo	carlo	PROPN
cuesj-252	60	30	.	.	PUNCT
cuesj-252	61	1	the	the	DET
cuesj-252	61	2	weight	weight	NOUN
cuesj-252	61	3	calculated	calculate	VERB
cuesj-252	61	4	from	from	ADP
cuesj-252	61	5	the	the	DET
cuesj-252	61	6	variable	variable	ADJ
cuesj-252	61	7	weights	weight	NOUN
cuesj-252	61	8	sampled	sample	VERB
cuesj-252	61	9	from	from	ADP
cuesj-252	61	10	posterior	posterior	ADJ
cuesj-252	61	11	distributions	distribution	NOUN
cuesj-252	61	12	instead	instead	ADV
cuesj-252	61	13	of	of	ADP
cuesj-252	61	14	being	be	AUX
cuesj-252	61	15	obtained	obtain	VERB
cuesj-252	61	16	from	from	ADP
cuesj-252	61	17	a	a	DET
cuesj-252	61	18	fixed	fix	VERB
cuesj-252	61	19	value	value	NOUN
cuesj-252	61	20	.	.	PUNCT
cuesj-252	62	1	therefore	therefore	ADV
cuesj-252	62	2	,	,	PUNCT
cuesj-252	62	3	in	in	ADP
cuesj-252	62	4	all	all	DET
cuesj-252	62	5	iterations	iteration	NOUN
cuesj-252	62	6	of	of	ADP
cuesj-252	62	7	the	the	DET
cuesj-252	62	8	outcome	outcome	NOUN
cuesj-252	62	9	models	model	NOUN
cuesj-252	62	10	,	,	PUNCT
cuesj-252	62	11	various	various	ADJ
cuesj-252	62	12	weights	weight	NOUN
cuesj-252	62	13	values	value	NOUN
cuesj-252	62	14	were	be	AUX
cuesj-252	62	15	gained	gain	VERB
cuesj-252	62	16	.	.	PUNCT
cuesj-252	63	1	ignoring	ignore	VERB
cuesj-252	63	2	any	any	DET
cuesj-252	63	3	uncertainty	uncertainty	NOUN
cuesj-252	63	4	between	between	ADP
cuesj-252	63	5	variable	variable	NOUN
cuesj-252	63	6	and	and	CCONJ
cuesj-252	63	7	fixed	fix	VERB
cuesj-252	63	8	weights	weight	NOUN
cuesj-252	63	9	was	be	AUX
cuesj-252	63	10	examined	examine	VERB
cuesj-252	63	11	to	to	PART
cuesj-252	63	12	determine	determine	VERB
cuesj-252	63	13	if	if	SCONJ
cuesj-252	63	14	there	there	PRON
cuesj-252	63	15	were	be	VERB
cuesj-252	63	16	any	any	DET
cuesj-252	63	17	issues	issue	NOUN
cuesj-252	63	18	.	.	PUNCT
cuesj-252	64	1	consequently	consequently	ADV
cuesj-252	64	2	,	,	PUNCT
cuesj-252	64	3	uncertainties	uncertainty	NOUN
cuesj-252	64	4	were	be	AUX
cuesj-252	64	5	included	include	VERB
cuesj-252	64	6	in	in	ADP
cuesj-252	64	7	the	the	DET
cuesj-252	64	8	weight	weight	NOUN
cuesj-252	64	9	value	value	NOUN
cuesj-252	64	10	using	use	VERB
cuesj-252	64	11	variable	variable	ADJ
cuesj-252	64	12	weights	weight	NOUN
cuesj-252	64	13	.	.	PUNCT
cuesj-252	65	1	in	in	ADP
cuesj-252	65	2	addition	addition	NOUN
cuesj-252	65	3	,	,	PUNCT
cuesj-252	65	4	weights	weight	NOUN
cuesj-252	65	5	were	be	AUX
cuesj-252	65	6	standardized	standardize	VERB
cuesj-252	65	7	(	(	PUNCT
cuesj-252	65	8	and	and	CCONJ
cuesj-252	65	9	multiplied	multiply	VERB
cuesj-252	65	10	by	by	ADP
cuesj-252	65	11	the	the	DET
cuesj-252	65	12	number	number	NOUN
cuesj-252	65	13	of	of	ADP
cuesj-252	65	14	observations	observation	NOUN
cuesj-252	65	15	/	/	SYM
cuesj-252	65	16	total	total	ADJ
cuesj-252	65	17	number	number	NOUN
cuesj-252	65	18	of	of	ADP
cuesj-252	65	19	the	the	DET
cuesj-252	65	20	complete	complete	ADJ
cuesj-252	65	21	population	population	NOUN
cuesj-252	65	22	)	)	PUNCT
cuesj-252	65	23	.	.	PUNCT
cuesj-252	66	1	this	this	PRON
cuesj-252	66	2	results	result	VERB
cuesj-252	66	3	from	from	ADP
cuesj-252	66	4	the	the	DET
cuesj-252	66	5	total	total	NOUN
cuesj-252	66	6	of	of	ADP
cuesj-252	66	7	the	the	DET
cuesj-252	66	8	weights	weight	NOUN
cuesj-252	66	9	being	be	AUX
cuesj-252	66	10	equal	equal	ADJ
cuesj-252	66	11	to	to	ADP
cuesj-252	66	12	the	the	DET
cuesj-252	66	13	sums	sum	NOUN
cuesj-252	66	14	of	of	ADP
cuesj-252	66	15	the	the	DET
cuesj-252	66	16	sample	sample	NOUN
cuesj-252	66	17	sizes	size	NOUN
cuesj-252	66	18	.	.	PUNCT
cuesj-252	67	1	if	if	SCONJ
cuesj-252	67	2	the	the	DET
cuesj-252	67	3	weights	weight	NOUN
cuesj-252	67	4	are	be	AUX
cuesj-252	67	5	not	not	PART
cuesj-252	67	6	standardized	standardize	VERB
cuesj-252	67	7	,	,	PUNCT
cuesj-252	67	8	the	the	DET
cuesj-252	67	9	sum	sum	NOUN
cuesj-252	67	10	of	of	ADP
cuesj-252	67	11	the	the	DET
cuesj-252	67	12	weight	weight	NOUN
cuesj-252	67	13	is	be	AUX
cuesj-252	67	14	then	then	ADV
cuesj-252	67	15	equal	equal	ADJ
cuesj-252	67	16	to	to	ADP
cuesj-252	67	17	the	the	DET
cuesj-252	67	18	entire	entire	ADJ
cuesj-252	67	19	kadir	kadir	NOUN
cuesj-252	67	20	:	:	PUNCT
cuesj-252	67	21	likelihood	likelihood	NOUN
cuesj-252	67	22	approach	approach	NOUN
cuesj-252	67	23	for	for	ADP
cuesj-252	67	24	bayesian	bayesian	NOUN
cuesj-252	67	25	logistic	logistic	NOUN
cuesj-252	67	26	weighted	weight	VERB
cuesj-252	67	27	model	model	NOUN
cuesj-252	67	28	11	11	NUM
cuesj-252	67	29	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-252	67	30	cuesj	cuesj	NOUN
cuesj-252	67	31	2020	2020	NUM
cuesj-252	67	32	,	,	PUNCT
cuesj-252	67	33	4	4	NUM
cuesj-252	67	34	(	(	PUNCT
cuesj-252	67	35	2	2	NUM
cuesj-252	67	36	):	):	PUNCT
cuesj-252	67	37	9	9	NUM
cuesj-252	67	38	-	-	SYM
cuesj-252	67	39	12	12	NUM
cuesj-252	67	40	population	population	NOUN
cuesj-252	67	41	instead	instead	ADV
cuesj-252	67	42	of	of	ADP
cuesj-252	67	43	the	the	DET
cuesj-252	67	44	total	total	ADJ
cuesj-252	67	45	amount	amount	NOUN
cuesj-252	67	46	of	of	ADP
cuesj-252	67	47	observations	observation	NOUN
cuesj-252	67	48	,	,	PUNCT
cuesj-252	67	49	meaning	mean	VERB
cuesj-252	67	50	that	that	SCONJ
cuesj-252	67	51	uncertainty	uncertainty	NOUN
cuesj-252	67	52	(	(	PUNCT
cuesj-252	67	53	i.e.	i.e.	X
cuesj-252	67	54	,	,	PUNCT
cuesj-252	67	55	standard	standard	ADJ
cuesj-252	67	56	deviation	deviation	NOUN
cuesj-252	67	57	and	and	CCONJ
cuesj-252	67	58	standard	standard	ADJ
cuesj-252	67	59	error	error	NOUN
cuesj-252	67	60	)	)	PUNCT
cuesj-252	67	61	in	in	ADP
cuesj-252	67	62	the	the	DET
cuesj-252	67	63	model	model	NOUN
cuesj-252	67	64	without	without	ADP
cuesj-252	67	65	standardization	standardization	NOUN
cuesj-252	67	66	will	will	AUX
cuesj-252	67	67	be	be	AUX
cuesj-252	67	68	underestimated	underestimate	VERB
cuesj-252	67	69	.	.	PUNCT
cuesj-252	68	1	thus	thus	ADV
cuesj-252	68	2	,	,	PUNCT
cuesj-252	68	3	in	in	ADP
cuesj-252	68	4	this	this	DET
cuesj-252	68	5	project	project	NOUN
cuesj-252	68	6	,	,	PUNCT
cuesj-252	68	7	the	the	DET
cuesj-252	68	8	weight	weight	NOUN
cuesj-252	68	9	is	be	AUX
cuesj-252	68	10	standardized	standardize	VERB
cuesj-252	68	11	.	.	PUNCT
cuesj-252	69	1	in	in	ADP
cuesj-252	69	2	these	these	DET
cuesj-252	69	3	analyses	analysis	NOUN
cuesj-252	69	4	,	,	PUNCT
cuesj-252	69	5	complete	complete	ADJ
cuesj-252	69	6	cases	case	NOUN
cuesj-252	69	7	are	be	AUX
cuesj-252	69	8	weighted	weight	VERB
cuesj-252	69	9	by	by	ADP
cuesj-252	69	10	the	the	DET
cuesj-252	69	11	inverse	inverse	ADJ
cuesj-252	69	12	probability	probability	NOUN
cuesj-252	69	13	of	of	ADP
cuesj-252	69	14	there	there	PRON
cuesj-252	69	15	being	be	AUX
cuesj-252	69	16	complete	complete	ADJ
cuesj-252	69	17	cases	case	NOUN
cuesj-252	69	18	.	.	PUNCT
cuesj-252	70	1	two	two	NUM
cuesj-252	70	2	logistic	logistic	ADJ
cuesj-252	70	3	regression	regression	NOUN
cuesj-252	70	4	models	model	NOUN
cuesj-252	70	5	were	be	AUX
cuesj-252	70	6	operated	operate	VERB
cuesj-252	70	7	at	at	ADP
cuesj-252	70	8	the	the	DET
cuesj-252	70	9	same	same	ADJ
cuesj-252	70	10	time	time	NOUN
cuesj-252	70	11	for	for	ADP
cuesj-252	70	12	both	both	DET
cuesj-252	70	13	outcome	outcome	NOUN
cuesj-252	70	14	and	and	CCONJ
cuesj-252	70	15	response	response	NOUN
cuesj-252	70	16	.	.	PUNCT
cuesj-252	71	1	a	a	DET
cuesj-252	71	2	covariate	covariate	NOUN
cuesj-252	71	3	of	of	ADP
cuesj-252	71	4	mother	mother	NOUN
cuesj-252	71	5	birth	birth	NOUN
cuesj-252	71	6	age	age	NOUN
cuesj-252	71	7	,	,	PUNCT
cuesj-252	71	8	sex	sex	NOUN
cuesj-252	71	9	,	,	PUNCT
cuesj-252	71	10	gestational	gestational	ADJ
cuesj-252	71	11	age	age	NOUN
cuesj-252	71	12	,	,	PUNCT
cuesj-252	71	13	and	and	CCONJ
cuesj-252	71	14	birth	birth	VERB
cuesj-252	71	15	weight	weight	NOUN
cuesj-252	71	16	z	z	PROPN
cuesj-252	71	17	-	-	PUNCT
cuesj-252	71	18	scores	score	NOUN
cuesj-252	71	19	was	be	AUX
cuesj-252	71	20	used	use	VERB
cuesj-252	71	21	in	in	ADP
cuesj-252	71	22	the	the	DET
cuesj-252	71	23	response	response	NOUN
cuesj-252	71	24	model	model	NOUN
cuesj-252	71	25	.	.	PUNCT
cuesj-252	72	1	let	let	VERB
cuesj-252	72	2	,	,	PUNCT
cuesj-252	72	3	ri	ri	PROPN
cuesj-252	72	4	denotes	denote	VERB
cuesj-252	72	5	the	the	DET
cuesj-252	72	6	outcomes	outcome	NOUN
cuesj-252	72	7	(	(	PUNCT
cuesj-252	72	8	response	response	NOUN
cuesj-252	72	9	(	(	PUNCT
cuesj-252	72	10	infants	infant	NOUN
cuesj-252	72	11	where	where	SCONJ
cuesj-252	72	12	the	the	DET
cuesj-252	72	13	developmental	developmental	ADJ
cuesj-252	72	14	questionnaire	questionnaire	NOUN
cuesj-252	72	15	was	be	AUX
cuesj-252	72	16	responded	respond	VERB
cuesj-252	72	17	to)/	to)/	DET
cuesj-252	72	18	non	non	ADJ
cuesj-252	72	19	-	-	NOUN
cuesj-252	72	20	response	response	NOUN
cuesj-252	73	1	[	[	X
cuesj-252	73	2	infants	infant	NOUN
cuesj-252	73	3	where	where	SCONJ
cuesj-252	73	4	the	the	DET
cuesj-252	73	5	developmental	developmental	ADJ
cuesj-252	73	6	questionnaire	questionnaire	NOUN
cuesj-252	73	7	was	be	AUX
cuesj-252	73	8	not	not	PART
cuesj-252	73	9	responded	respond	VERB
cuesj-252	73	10	to	to	ADP
cuesj-252	73	11	]	]	PUNCT
cuesj-252	73	12	)	)	PUNCT
cuesj-252	73	13	.	.	PUNCT
cuesj-252	74	1	the	the	DET
cuesj-252	74	2	outcome	outcome	NOUN
cuesj-252	74	3	was	be	AUX
cuesj-252	74	4	modeled	model	VERB
cuesj-252	74	5	with	with	ADP
cuesj-252	74	6	the	the	DET
cuesj-252	74	7	assumption	assumption	NOUN
cuesj-252	74	8	of	of	ADP
cuesj-252	74	9	the	the	DET
cuesj-252	74	10	bernoulli	bernoulli	NOUN
cuesj-252	74	11	distribution	distribution	NOUN
cuesj-252	74	12	.	.	PUNCT
cuesj-252	75	1	ri	ri	X
cuesj-252	75	2	~	~	PUNCT
cuesj-252	75	3	bernoulli(qi	bernoulli(qi	X
cuesj-252	75	4	)	)	PUNCT
cuesj-252	75	5	(	(	PUNCT
cuesj-252	75	6	3	3	X
cuesj-252	75	7	)	)	PUNCT
cuesj-252	75	8	where	where	SCONJ
cuesj-252	75	9	,	,	PUNCT
cuesj-252	75	10	0logit	0logit	NUM
cuesj-252	75	11	1	1	NUM
cuesj-252	75	12			NOUN
cuesj-252	75	13			PUNCT
cuesj-252	76	1	=	=	PUNCT
cuesj-252	77	1	+	+	ADJ
cuesj-252	77	2			NOUN
cuesj-252	77	3	−	−	PROPN
cuesj-252	77	4			PUNCT
cuesj-252	78	1	i	i	PRON
cuesj-252	78	2	i	i	PRON
cuesj-252	78	3	q	q	VERB
cuesj-252	78	4	a	a	DET
cuesj-252	78	5	ax	ax	NOUN
cuesj-252	78	6	q	q	NOUN
cuesj-252	78	7	when	when	SCONJ
cuesj-252	78	8	statistical	statistical	ADJ
cuesj-252	78	9	models	model	NOUN
cuesj-252	78	10	for	for	ADP
cuesj-252	78	11	weight	weight	NOUN
cuesj-252	78	12	have	have	AUX
cuesj-252	78	13	been	be	AUX
cuesj-252	78	14	recognized	recognize	VERB
cuesj-252	78	15	,	,	PUNCT
cuesj-252	78	16	it	it	PRON
cuesj-252	78	17	can	can	AUX
cuesj-252	78	18	then	then	ADV
cuesj-252	78	19	be	be	AUX
cuesj-252	78	20	used	use	VERB
cuesj-252	78	21	in	in	ADP
cuesj-252	78	22	developmental	developmental	ADJ
cuesj-252	78	23	delay	delay	NOUN
cuesj-252	78	24	model	model	NOUN
cuesj-252	78	25	analyses	analysis	NOUN
cuesj-252	78	26	to	to	PART
cuesj-252	78	27	be	be	AUX
cuesj-252	78	28	run	run	VERB
cuesj-252	78	29	alongside	alongside	ADP
cuesj-252	78	30	the	the	DET
cuesj-252	78	31	dataset	dataset	NOUN
cuesj-252	78	32	.	.	PUNCT
cuesj-252	79	1	nonetheless	nonetheless	ADV
cuesj-252	79	2	,	,	PUNCT
cuesj-252	79	3	weighting	weight	VERB
cuesj-252	79	4	is	be	AUX
cuesj-252	79	5	vital	vital	ADJ
cuesj-252	79	6	and	and	CCONJ
cuesj-252	79	7	,	,	PUNCT
cuesj-252	79	8	thus	thus	ADV
cuesj-252	79	9	,	,	PUNCT
cuesj-252	79	10	the	the	DET
cuesj-252	79	11	amount	amount	NOUN
cuesj-252	79	12	of	of	ADP
cuesj-252	79	13	information	information	NOUN
cuesj-252	79	14	is	be	AUX
cuesj-252	79	15	required	require	VERB
cuesj-252	79	16	to	to	PART
cuesj-252	79	17	account	account	VERB
cuesj-252	79	18	for	for	ADP
cuesj-252	79	19	the	the	DET
cuesj-252	79	20	weight	weight	NOUN
cuesj-252	79	21	relying	rely	VERB
cuesj-252	79	22	on	on	ADP
cuesj-252	79	23	particular	particular	ADJ
cuesj-252	79	24	parameters	parameter	NOUN
cuesj-252	79	25	being	be	AUX
cuesj-252	79	26	considered	consider	VERB
cuesj-252	79	27	.	.	PUNCT
cuesj-252	80	1	inference	inference	NOUN
cuesj-252	80	2	is	be	AUX
cuesj-252	80	3	normally	normally	ADV
cuesj-252	80	4	changed	change	VERB
cuesj-252	80	5	by	by	ADP
cuesj-252	80	6	multiplying	multiply	VERB
cuesj-252	80	7	the	the	DET
cuesj-252	80	8	contributions	contribution	NOUN
cuesj-252	80	9	of	of	ADP
cuesj-252	80	10	every	every	DET
cuesj-252	80	11	infant	infant	NOUN
cuesj-252	80	12	to	to	ADP
cuesj-252	80	13	a	a	DET
cuesj-252	80	14	statistic	statistic	NOUN
cuesj-252	80	15	by	by	ADP
cuesj-252	80	16	its	its	PRON
cuesj-252	80	17	statistical	statistical	ADJ
cuesj-252	80	18	weight	weight	NOUN
cuesj-252	80	19	.	.	PUNCT
cuesj-252	81	1	for	for	ADP
cuesj-252	81	2	modeling	model	VERB
cuesj-252	81	3	outcome	outcome	NOUN
cuesj-252	81	4	and	and	CCONJ
cuesj-252	81	5	weight	weight	NOUN
cuesj-252	81	6	,	,	PUNCT
cuesj-252	81	7	each	each	DET
cuesj-252	81	8	individual	individual	NOUN
cuesj-252	81	9	’s	’s	PART
cuesj-252	81	10	outcome	outcome	NOUN
cuesj-252	81	11	variable	variable	ADJ
cuesj-252	81	12	value	value	NOUN
cuesj-252	81	13	was	be	AUX
cuesj-252	81	14	multiplied	multiply	VERB
cuesj-252	81	15	by	by	ADP
cuesj-252	81	16	the	the	DET
cuesj-252	81	17	individual	individual	NOUN
cuesj-252	81	18	’s	’s	PART
cuesj-252	81	19	weight	weight	NOUN
cuesj-252	81	20	.	.	PUNCT
cuesj-252	82	1	ipw	ipw	PROPN
cuesj-252	82	2	for	for	ADP
cuesj-252	82	3	each	each	PRON
cuesj-252	82	4	of	of	ADP
cuesj-252	82	5	the	the	DET
cuesj-252	82	6	infants	infant	NOUN
cuesj-252	82	7	is	be	AUX
cuesj-252	82	8	calculated	calculate	VERB
cuesj-252	82	9	using	use	VERB
cuesj-252	82	10	1	1	NUM
cuesj-252	82	11	/	/	SYM
cuesj-252	82	12	probability	probability	NOUN
cuesj-252	82	13	of	of	ADP
cuesj-252	82	14	responses	response	NOUN
cuesj-252	82	15	;	;	PUNCT
cuesj-252	82	16	the	the	DET
cuesj-252	82	17	ipw	ipw	PROPN
cuesj-252	82	18	was	be	AUX
cuesj-252	82	19	then	then	ADV
cuesj-252	82	20	standardized	standardize	VERB
cuesj-252	82	21	.	.	PUNCT
cuesj-252	83	1	therefore	therefore	ADV
cuesj-252	83	2	,	,	PUNCT
cuesj-252	83	3	the	the	DET
cuesj-252	83	4	likelihood	likelihood	NOUN
cuesj-252	83	5	functions	function	NOUN
cuesj-252	83	6	created	create	VERB
cuesj-252	83	7	in	in	ADP
cuesj-252	83	8	winbugs	winbug	NOUN
cuesj-252	83	9	and	and	CCONJ
cuesj-252	83	10	is	be	AUX
cuesj-252	83	11	thus	thus	ADV
cuesj-252	83	12	:	:	PUNCT
cuesj-252	83	13	*	*	PUNCT
cuesj-252	83	14	(	(	PUNCT
cuesj-252	83	15	1	1	X
cuesj-252	83	16	)	)	PUNCT
cuesj-252	83	17	=	=	VERB
cuesj-252	84	1	−y	−y	PROPN
cuesj-252	84	2	ipw	ipw	PROPN
cuesj-252	84	3	y*ipw	y*ipw	ADP
cuesj-252	84	4	il	il	PROPN
cuesj-252	84	5	p	p	PROPN
cuesj-252	84	6	p	p	X
cuesj-252	84	7	(	(	PUNCT
cuesj-252	84	8	4	4	NUM
cuesj-252	84	9	)	)	PUNCT
cuesj-252	84	10	p	p	NOUN
cuesj-252	84	11	is	be	AUX
cuesj-252	84	12	the	the	DET
cuesj-252	84	13	probability	probability	NOUN
cuesj-252	84	14	of	of	ADP
cuesj-252	84	15	babies	baby	NOUN
cuesj-252	84	16	surviving	survive	VERB
cuesj-252	84	17	with	with	ADP
cuesj-252	84	18	developmentally	developmentally	ADV
cuesj-252	84	19	delay	delay	NOUN
cuesj-252	84	20	issues	issue	NOUN
cuesj-252	84	21	,	,	PUNCT
cuesj-252	84	22	y	y	PROPN
cuesj-252	84	23	is	be	AUX
cuesj-252	84	24	the	the	DET
cuesj-252	84	25	outcome	outcome	NOUN
cuesj-252	84	26	variable	variable	NOUN
cuesj-252	84	27	,	,	PUNCT
cuesj-252	84	28	and	and	CCONJ
cuesj-252	84	29	ipw	ipw	PROPN
cuesj-252	84	30	is	be	AUX
cuesj-252	84	31	the	the	DET
cuesj-252	84	32	ipw	ipw	PROPN
cuesj-252	84	33	.	.	PUNCT
cuesj-252	85	1	five	five	NUM
cuesj-252	85	2	hundred	hundred	NUM
cuesj-252	85	3	seventy	seventy	NUM
cuesj-252	85	4	infants	infant	NOUN
cuesj-252	85	5	featured	feature	VERB
cuesj-252	85	6	in	in	ADP
cuesj-252	85	7	the	the	DET
cuesj-252	85	8	response	response	NOUN
cuesj-252	85	9	model	model	NOUN
cuesj-252	85	10	.	.	PUNCT
cuesj-252	86	1	yet	yet	ADV
cuesj-252	86	2	,	,	PUNCT
cuesj-252	86	3	only	only	ADV
cuesj-252	86	4	235	235	NUM
cuesj-252	86	5	babies	baby	NOUN
cuesj-252	86	6	were	be	AUX
cuesj-252	86	7	used	use	VERB
cuesj-252	86	8	in	in	ADP
cuesj-252	86	9	the	the	DET
cuesj-252	86	10	outcome	outcome	NOUN
cuesj-252	86	11	model	model	NOUN
cuesj-252	86	12	analysis	analysis	NOUN
cuesj-252	86	13	(	(	PUNCT
cuesj-252	86	14	those	those	DET
cuesj-252	86	15	babies	baby	NOUN
cuesj-252	86	16	known	know	VERB
cuesj-252	86	17	to	to	PART
cuesj-252	86	18	be	be	AUX
cuesj-252	86	19	alive	alive	ADJ
cuesj-252	86	20	)	)	PUNCT
cuesj-252	86	21	.	.	PUNCT
cuesj-252	87	1	we	we	PRON
cuesj-252	87	2	have	have	AUX
cuesj-252	87	3	used	use	VERB
cuesj-252	87	4	ipws	ipws	NOUN
cuesj-252	87	5	as	as	ADP
cuesj-252	87	6	adjustment	adjustment	NOUN
cuesj-252	87	7	factors	factor	NOUN
cuesj-252	87	8	for	for	ADP
cuesj-252	87	9	babies	baby	NOUN
cuesj-252	87	10	about	about	ADP
cuesj-252	87	11	which	which	PRON
cuesj-252	87	12	we	we	PRON
cuesj-252	87	13	do	do	AUX
cuesj-252	87	14	not	not	PART
cuesj-252	87	15	have	have	VERB
cuesj-252	87	16	cognitive	cognitive	ADJ
cuesj-252	87	17	developmental	developmental	ADJ
cuesj-252	87	18	delay	delay	NOUN
cuesj-252	87	19	information	information	NOUN
cuesj-252	87	20	.	.	PUNCT
cuesj-252	88	1	we	we	PRON
cuesj-252	88	2	put	put	VERB
cuesj-252	88	3	weights	weight	NOUN
cuesj-252	88	4	on	on	ADP
cuesj-252	88	5	the	the	DET
cuesj-252	88	6	likelihood	likelihood	NOUN
cuesj-252	88	7	function	function	NOUN
cuesj-252	88	8	using	use	VERB
cuesj-252	88	9	winbugs	winbug	NOUN
cuesj-252	88	10	software	software	NOUN
cuesj-252	88	11	.	.	PUNCT
cuesj-252	89	1	we	we	PRON
cuesj-252	89	2	repeated	repeat	VERB
cuesj-252	89	3	the	the	DET
cuesj-252	89	4	analysis	analysis	NOUN
cuesj-252	89	5	using	use	VERB
cuesj-252	89	6	frequentist	frequentist	NOUN
cuesj-252	89	7	logistic	logistic	ADJ
cuesj-252	89	8	regression	regression	NOUN
cuesj-252	89	9	using	use	VERB
cuesj-252	89	10	variable	variable	ADJ
cuesj-252	89	11	weights	weight	NOUN
cuesj-252	89	12	.	.	PUNCT
cuesj-252	90	1	we	we	PRON
cuesj-252	90	2	obtained	obtain	VERB
cuesj-252	90	3	greater	great	ADJ
cuesj-252	90	4	precision	precision	NOUN
cuesj-252	90	5	in	in	ADP
cuesj-252	90	6	results	result	NOUN
cuesj-252	90	7	and	and	CCONJ
cuesj-252	90	8	standard	standard	ADJ
cuesj-252	90	9	deviation	deviation	NOUN
cuesj-252	90	10	of	of	ADP
cuesj-252	90	11	parameter	parameter	NOUN
cuesj-252	90	12	estimates	estimate	NOUN
cuesj-252	90	13	as	as	SCONJ
cuesj-252	90	14	it	it	PRON
cuesj-252	90	15	is	be	AUX
cuesj-252	90	16	shown	show	VERB
cuesj-252	90	17	in	in	ADP
cuesj-252	90	18	table	table	NOUN
cuesj-252	90	19	1	1	NUM
cuesj-252	90	20	,	,	PUNCT
cuesj-252	90	21	which	which	PRON
cuesj-252	90	22	are	be	AUX
cuesj-252	90	23	less	less	ADJ
cuesj-252	90	24	in	in	ADP
cuesj-252	90	25	the	the	DET
cuesj-252	90	26	posterior	posterior	NOUN
cuesj-252	90	27	weighted	weight	VERB
cuesj-252	90	28	model	model	NOUN
cuesj-252	90	29	in	in	ADP
cuesj-252	90	30	comparison	comparison	NOUN
cuesj-252	90	31	with	with	ADP
cuesj-252	90	32	frequent	frequent	ADJ
cuesj-252	90	33	analysis	analysis	NOUN
cuesj-252	90	34	.	.	PUNCT
cuesj-252	91	1	discussion	discussion	NOUN
cuesj-252	91	2	we	we	PRON
cuesj-252	91	3	have	have	AUX
cuesj-252	91	4	developed	develop	VERB
cuesj-252	91	5	a	a	DET
cuesj-252	91	6	likelihood	likelihood	NOUN
cuesj-252	91	7	-	-	PUNCT
cuesj-252	91	8	based	base	VERB
cuesj-252	91	9	approach	approach	NOUN
cuesj-252	91	10	to	to	ADP
cuesj-252	91	11	place	place	NOUN
cuesj-252	91	12	weights	weight	NOUN
cuesj-252	91	13	which	which	PRON
cuesj-252	91	14	were	be	AUX
cuesj-252	91	15	calculated	calculate	VERB
cuesj-252	91	16	from	from	ADP
cuesj-252	91	17	response	response	NOUN
cuesj-252	91	18	models	model	NOUN
cuesj-252	91	19	into	into	ADP
cuesj-252	91	20	outcome	outcome	NOUN
cuesj-252	91	21	models	model	NOUN
cuesj-252	91	22	using	use	VERB
cuesj-252	91	23	logistic	logistic	ADJ
cuesj-252	91	24	regression	regression	NOUN
cuesj-252	91	25	.	.	PUNCT
cuesj-252	92	1	it	it	PRON
cuesj-252	92	2	is	be	AUX
cuesj-252	92	3	noticed	notice	VERB
cuesj-252	92	4	that	that	SCONJ
cuesj-252	92	5	unweighted	unweighted	ADJ
cuesj-252	92	6	models	model	NOUN
cuesj-252	92	7	produce	produce	VERB
cuesj-252	92	8	biased	biased	ADJ
cuesj-252	92	9	results	result	NOUN
cuesj-252	92	10	.	.	PUNCT
cuesj-252	93	1	we	we	PRON
cuesj-252	93	2	have	have	AUX
cuesj-252	93	3	realized	realize	VERB
cuesj-252	93	4	that	that	SCONJ
cuesj-252	93	5	a	a	DET
cuesj-252	93	6	weighted	weight	VERB
cuesj-252	93	7	model	model	NOUN
cuesj-252	93	8	would	would	AUX
cuesj-252	93	9	provide	provide	VERB
cuesj-252	93	10	more	more	ADV
cuesj-252	93	11	precise	precise	ADJ
cuesj-252	93	12	results	result	NOUN
cuesj-252	93	13	in	in	ADP
cuesj-252	93	14	terms	term	NOUN
cuesj-252	93	15	of	of	ADP
cuesj-252	93	16	odds	odd	NOUN
cuesj-252	93	17	ratio	ratio	NOUN
cuesj-252	93	18	and	and	CCONJ
cuesj-252	93	19	uncertainty	uncertainty	NOUN
cuesj-252	93	20	.	.	PUNCT
cuesj-252	94	1	ipw	ipw	PROPN
cuesj-252	94	2	is	be	AUX
cuesj-252	94	3	one	one	NUM
cuesj-252	94	4	of	of	ADP
cuesj-252	94	5	the	the	DET
cuesj-252	94	6	many	many	ADJ
cuesj-252	94	7	available	available	ADJ
cuesj-252	94	8	approaches	approach	NOUN
cuesj-252	94	9	for	for	ADP
cuesj-252	94	10	reducing	reduce	VERB
cuesj-252	94	11	bias	bias	NOUN
cuesj-252	94	12	using	use	VERB
cuesj-252	94	13	complete	complete	ADJ
cuesj-252	94	14	case	case	NOUN
cuesj-252	94	15	analysis	analysis	NOUN
cuesj-252	94	16	.	.	PUNCT
cuesj-252	95	1	here	here	ADV
cuesj-252	95	2	,	,	PUNCT
cuesj-252	95	3	a	a	DET
cuesj-252	95	4	complete	complete	ADJ
cuesj-252	95	5	case	case	NOUN
cuesj-252	95	6	is	be	AUX
cuesj-252	95	7	weighted	weight	VERB
cuesj-252	95	8	by	by	ADP
cuesj-252	95	9	probability	probability	NOUN
cuesj-252	95	10	inverse	inverse	NOUN
cuesj-252	95	11	of	of	ADP
cuesj-252	95	12	complete	complete	ADJ
cuesj-252	95	13	cases	case	NOUN
cuesj-252	95	14	.	.	PUNCT
cuesj-252	96	1	even	even	ADV
cuesj-252	96	2	though	though	SCONJ
cuesj-252	96	3	weighting	weighting	NOUN
cuesj-252	96	4	is	be	AUX
cuesj-252	96	5	often	often	ADV
cuesj-252	96	6	used	use	VERB
cuesj-252	96	7	in	in	ADP
cuesj-252	96	8	designing	design	VERB
cuesj-252	96	9	and	and	CCONJ
cuesj-252	96	10	analyzing	analyze	VERB
cuesj-252	96	11	surveys	survey	NOUN
cuesj-252	96	12	,	,	PUNCT
cuesj-252	96	13	using	use	VERB
cuesj-252	96	14	it	it	PRON
cuesj-252	96	15	in	in	ADP
cuesj-252	96	16	analyses	analysis	NOUN
cuesj-252	96	17	of	of	ADP
cuesj-252	96	18	missing	miss	VERB
cuesj-252	96	19	data	datum	NOUN
cuesj-252	96	20	not	not	PART
cuesj-252	96	21	as	as	ADV
cuesj-252	96	22	well	well	ADV
cuesj-252	96	23	recognized	recognize	VERB
cuesj-252	96	24	,	,	PUNCT
cuesj-252	96	25	as	as	SCONJ
cuesj-252	96	26	the	the	DET
cuesj-252	96	27	ipw	ipw	PROPN
cuesj-252	96	28	fact	fact	NOUN
cuesj-252	96	29	parameter	parameter	NOUN
cuesj-252	96	30	estimates	estimate	NOUN
cuesj-252	96	31	can	can	AUX
cuesj-252	96	32	be	be	AUX
cuesj-252	96	33	inefficient	inefficient	ADJ
cuesj-252	96	34	in	in	ADP
cuesj-252	96	35	regard	regard	NOUN
cuesj-252	96	36	to	to	ADP
cuesj-252	96	37	probability	probability	NOUN
cuesj-252	96	38	-	-	PUNCT
cuesj-252	96	39	based	base	VERB
cuesj-252	96	40	analysis.[10	analysis.[10	NOUN
cuesj-252	96	41	]	]	PUNCT
cuesj-252	96	42	the	the	DET
cuesj-252	96	43	resulting	result	VERB
cuesj-252	96	44	estimate	estimate	NOUN
cuesj-252	96	45	is	be	AUX
cuesj-252	96	46	frequently	frequently	ADV
cuesj-252	96	47	sensitive	sensitive	ADJ
cuesj-252	96	48	to	to	ADP
cuesj-252	96	49	the	the	DET
cuesj-252	96	50	exact	exact	ADJ
cuesj-252	96	51	type	type	NOUN
cuesj-252	96	52	of	of	ADP
cuesj-252	96	53	models	model	NOUN
cuesj-252	96	54	for	for	ADP
cuesj-252	96	55	the	the	DET
cuesj-252	96	56	response	response	NOUN
cuesj-252	96	57	probabilities.[11	probabilities.[11	PROPN
cuesj-252	96	58	]	]	PUNCT
cuesj-252	96	59	in	in	ADP
cuesj-252	96	60	reality	reality	NOUN
cuesj-252	96	61	,	,	PUNCT
cuesj-252	96	62	the	the	DET
cuesj-252	96	63	greatest	great	ADJ
cuesj-252	96	64	concern	concern	NOUN
cuesj-252	96	65	of	of	ADP
cuesj-252	96	66	the	the	DET
cuesj-252	96	67	data	datum	NOUN
cuesj-252	96	68	analysis	analysis	NOUN
cuesj-252	96	69	is	be	AUX
cuesj-252	96	70	the	the	DET
cuesj-252	96	71	efficacy	efficacy	NOUN
cuesj-252	96	72	of	of	ADP
cuesj-252	96	73	the	the	DET
cuesj-252	96	74	ipw	ipw	PROPN
cuesj-252	96	75	approach	approach	NOUN
cuesj-252	96	76	regarding	regard	VERB
cuesj-252	96	77	the	the	DET
cuesj-252	96	78	likelihood	likelihood	NOUN
cuesj-252	96	79	approach	approach	NOUN
cuesj-252	96	80	.	.	PUNCT
cuesj-252	97	1	although	although	SCONJ
cuesj-252	97	2	some	some	DET
cuesj-252	97	3	methods	method	NOUN
cuesj-252	97	4	have	have	AUX
cuesj-252	97	5	been	be	AUX
cuesj-252	97	6	suggested	suggest	VERB
cuesj-252	97	7	for	for	ADP
cuesj-252	97	8	obtaining	obtain	VERB
cuesj-252	97	9	more	more	ADV
cuesj-252	97	10	efficient	efficient	ADJ
cuesj-252	97	11	and	and	CCONJ
cuesj-252	97	12	robust	robust	ADJ
cuesj-252	97	13	estimates	estimate	NOUN
cuesj-252	97	14	,	,	PUNCT
cuesj-252	97	15	this	this	DET
cuesj-252	97	16	approach	approach	NOUN
cuesj-252	97	17	has	have	AUX
cuesj-252	97	18	not	not	PART
cuesj-252	97	19	yet	yet	ADV
cuesj-252	97	20	been	be	AUX
cuesj-252	97	21	effectively	effectively	ADV
cuesj-252	97	22	developed	develop	VERB
cuesj-252	97	23	to	to	PART
cuesj-252	97	24	handle	handle	VERB
cuesj-252	97	25	more	more	ADJ
cuesj-252	97	26	than	than	ADP
cuesj-252	97	27	one	one	NUM
cuesj-252	97	28	situation	situation	NOUN
cuesj-252	97	29	.	.	PUNCT
cuesj-252	98	1	alternative	alternative	ADJ
cuesj-252	98	2	methods	method	NOUN
cuesj-252	98	3	could	could	AUX
cuesj-252	98	4	have	have	AUX
cuesj-252	98	5	been	be	AUX
cuesj-252	98	6	used	use	VERB
cuesj-252	98	7	in	in	ADP
cuesj-252	98	8	this	this	DET
cuesj-252	98	9	analysis	analysis	NOUN
cuesj-252	98	10	,	,	PUNCT
cuesj-252	98	11	for	for	ADP
cuesj-252	98	12	example	example	NOUN
cuesj-252	98	13	,	,	PUNCT
cuesj-252	98	14	doubly	doubly	ADV
cuesj-252	98	15	robust	robust	ADJ
cuesj-252	98	16	ipw	ipw	NOUN
cuesj-252	98	17	and	and	CCONJ
cuesj-252	98	18	multiple	multiple	ADJ
cuesj-252	98	19	imputation	imputation	NOUN
cuesj-252	98	20	.	.	PUNCT
cuesj-252	99	1	in	in	ADP
cuesj-252	99	2	addition	addition	NOUN
cuesj-252	99	3	,	,	PUNCT
cuesj-252	99	4	one	one	NUM
cuesj-252	99	5	disadvantage	disadvantage	NOUN
cuesj-252	99	6	of	of	ADP
cuesj-252	99	7	this	this	DET
cuesj-252	99	8	paper	paper	NOUN
cuesj-252	99	9	is	be	AUX
cuesj-252	99	10	the	the	DET
cuesj-252	99	11	assumption	assumption	NOUN
cuesj-252	99	12	that	that	SCONJ
cuesj-252	99	13	the	the	DET
cuesj-252	99	14	weight	weight	NOUN
cuesj-252	99	15	is	be	AUX
cuesj-252	99	16	known	know	VERB
cuesj-252	99	17	;	;	PUNCT
cuesj-252	99	18	we	we	PRON
cuesj-252	99	19	have	have	AUX
cuesj-252	99	20	ignored	ignore	VERB
cuesj-252	99	21	uncertainties	uncertainty	NOUN
cuesj-252	99	22	in	in	ADP
cuesj-252	99	23	the	the	DET
cuesj-252	99	24	weight	weight	NOUN
cuesj-252	99	25	.	.	PUNCT
cuesj-252	100	1	to	to	PART
cuesj-252	100	2	calculate	calculate	VERB
cuesj-252	100	3	ipw	ipw	PROPN
cuesj-252	100	4	estimator	estimator	PROPN
cuesj-252	100	5	standard	standard	PROPN
cuesj-252	100	6	error	error	NOUN
cuesj-252	100	7	,	,	PUNCT
cuesj-252	100	8	methods	method	NOUN
cuesj-252	100	9	like	like	ADP
cuesj-252	100	10	robust	robust	ADJ
cuesj-252	100	11	standard	standard	ADJ
cuesj-252	100	12	error	error	NOUN
cuesj-252	100	13	created	create	VERB
cuesj-252	100	14	by	by	ADP
cuesj-252	100	15	weighted	weighted	ADJ
cuesj-252	100	16	models	model	NOUN
cuesj-252	100	17	could	could	AUX
cuesj-252	100	18	have	have	AUX
cuesj-252	100	19	been	be	AUX
cuesj-252	100	20	used	use	VERB
cuesj-252	100	21	.	.	PUNCT
cuesj-252	101	1	other	other	ADJ
cuesj-252	101	2	methods	method	NOUN
cuesj-252	101	3	such	such	ADJ
cuesj-252	101	4	as	as	ADP
cuesj-252	101	5	bootstrapping	bootstrappe	VERB
cuesj-252	101	6	,	,	PUNCT
cuesj-252	101	7	sandwich	sandwich	NOUN
cuesj-252	101	8	,	,	PUNCT
cuesj-252	101	9	resampling	resample	VERB
cuesj-252	101	10	,	,	PUNCT
cuesj-252	101	11	and	and	CCONJ
cuesj-252	101	12	jackknife	jackknife	NOUN
cuesj-252	101	13	methods	method	NOUN
cuesj-252	101	14	are	be	AUX
cuesj-252	101	15	also	also	ADV
cuesj-252	101	16	possibilities	possibility	NOUN
cuesj-252	101	17	,	,	PUNCT
cuesj-252	101	18	although	although	SCONJ
cuesj-252	101	19	these	these	DET
cuesj-252	101	20	methods	method	NOUN
cuesj-252	101	21	require	require	VERB
cuesj-252	101	22	intensive	intensive	ADJ
cuesj-252	101	23	computations.[4,12	computations.[4,12	PROPN
cuesj-252	101	24	]	]	PUNCT
cuesj-252	101	25	references	reference	NOUN
cuesj-252	101	26	1	1	NUM
cuesj-252	101	27	.	.	PUNCT
cuesj-252	101	28	d.	d.	PROPN
cuesj-252	101	29	wolke	wolke	PROPN
cuesj-252	101	30	,	,	PUNCT
cuesj-252	101	31	b.	b.	PROPN
cuesj-252	101	32	sohne	sohne	PROPN
cuesj-252	101	33	,	,	PUNCT
cuesj-252	101	34	b.	b.	PROPN
cuesj-252	101	35	ohrt	ohrt	PROPN
cuesj-252	101	36	and	and	CCONJ
cuesj-252	101	37	k.	k.	PROPN
cuesj-252	101	38	riegel	riegel	PROPN
cuesj-252	101	39	.	.	PUNCT
cuesj-252	102	1	follow	follow	VERB
cuesj-252	102	2	-	-	PUNCT
cuesj-252	102	3	up	up	NOUN
cuesj-252	102	4	of	of	ADP
cuesj-252	102	5	preterm	preterm	ADJ
cuesj-252	102	6	children	child	NOUN
cuesj-252	102	7	:	:	PUNCT
cuesj-252	102	8	important	important	ADJ
cuesj-252	102	9	to	to	PART
cuesj-252	102	10	document	document	NOUN
cuesj-252	102	11	dropouts	dropout	NOUN
cuesj-252	102	12	.	.	PUNCT
cuesj-252	103	1	lancet	lancet	NOUN
cuesj-252	103	2	,	,	PUNCT
cuesj-252	103	3	vol	vol	NOUN
cuesj-252	103	4	.	.	PROPN
cuesj-252	103	5	345	345	NUM
cuesj-252	103	6	,	,	PUNCT
cuesj-252	103	7	no	no	INTJ
cuesj-252	103	8	.	.	NOUN
cuesj-252	103	9	8947	8947	NUM
cuesj-252	103	10	,	,	PUNCT
cuesj-252	103	11	p.	p.	NOUN
cuesj-252	103	12	447	447	NUM
cuesj-252	103	13	,	,	PUNCT
cuesj-252	103	14	1995	1995	NUM
cuesj-252	103	15	.	.	PUNCT
cuesj-252	104	1	2	2	NUM
cuesj-252	104	2	.	.	PUNCT
cuesj-252	104	3	s.	s.	PROPN
cuesj-252	104	4	johnson	johnson	PROPN
cuesj-252	104	5	,	,	PUNCT
cuesj-252	104	6	s.	s.	PROPN
cuesj-252	104	7	e.	e.	PROPN
cuesj-252	104	8	seaton	seaton	PROPN
cuesj-252	104	9	,	,	PUNCT
cuesj-252	104	10	b.	b.	PROPN
cuesj-252	104	11	n.	n.	PROPN
cuesj-252	104	12	manktelow	manktelow	PROPN
cuesj-252	104	13	,	,	PUNCT
cuesj-252	104	14	l.	l.	PROPN
cuesj-252	104	15	k.	k.	PROPN
cuesj-252	104	16	smith	smith	PROPN
cuesj-252	104	17	,	,	PUNCT
cuesj-252	104	18	d.	d.	PROPN
cuesj-252	104	19	field	field	PROPN
cuesj-252	104	20	,	,	PUNCT
cuesj-252	104	21	e.	e.	PROPN
cuesj-252	104	22	s.	s.	PROPN
cuesj-252	104	23	draper	draper	PROPN
cuesj-252	104	24	,	,	PUNCT
cuesj-252	104	25	n.	n.	PROPN
cuesj-252	104	26	marlow	marlow	PROPN
cuesj-252	104	27	and	and	CCONJ
cuesj-252	104	28	e.	e.	PROPN
cuesj-252	104	29	m.	m.	PROPN
cuesj-252	104	30	boyle	boyle	PROPN
cuesj-252	104	31	.	.	PUNCT
cuesj-252	105	1	telephone	telephone	NOUN
cuesj-252	105	2	interviews	interview	NOUN
cuesj-252	105	3	and	and	CCONJ
cuesj-252	105	4	online	online	ADJ
cuesj-252	105	5	questionnaires	questionnaire	NOUN
cuesj-252	105	6	can	can	AUX
cuesj-252	105	7	be	be	AUX
cuesj-252	105	8	used	use	VERB
cuesj-252	105	9	to	to	PART
cuesj-252	105	10	improve	improve	VERB
cuesj-252	105	11	neurodevelopmental	neurodevelopmental	ADJ
cuesj-252	105	12	follow	follow	VERB
cuesj-252	105	13	-	-	PUNCT
cuesj-252	105	14	up	up	ADP
cuesj-252	105	15	rates	rate	NOUN
cuesj-252	105	16	.	.	PUNCT
cuesj-252	106	1	bmc	bmc	ADJ
cuesj-252	106	2	research	research	NOUN
cuesj-252	106	3	notes	note	NOUN
cuesj-252	106	4	,	,	PUNCT
cuesj-252	106	5	vol	vol	NOUN
cuesj-252	106	6	.	.	PROPN
cuesj-252	106	7	7	7	NUM
cuesj-252	106	8	,	,	PUNCT
cuesj-252	106	9	p.	p.	NOUN
cuesj-252	106	10	219	219	NUM
cuesj-252	106	11	,	,	PUNCT
cuesj-252	106	12	2014	2014	NUM
cuesj-252	106	13	.	.	PUNCT
cuesj-252	107	1	3	3	X
cuesj-252	107	2	.	.	X
cuesj-252	107	3	d.	d.	PROPN
cuesj-252	107	4	b.	b.	PROPN
cuesj-252	107	5	rubin	rubin	PROPN
cuesj-252	107	6	.	.	PUNCT
cuesj-252	108	1	inference	inference	NOUN
cuesj-252	108	2	and	and	CCONJ
cuesj-252	108	3	missing	miss	VERB
cuesj-252	108	4	data	datum	NOUN
cuesj-252	108	5	.	.	PUNCT
cuesj-252	109	1	biometrika	biometrika	NOUN
cuesj-252	109	2	,	,	PUNCT
cuesj-252	109	3	vol	vol	NOUN
cuesj-252	109	4	.	.	PROPN
cuesj-252	109	5	63	63	NUM
cuesj-252	109	6	,	,	PUNCT
cuesj-252	109	7	no	no	INTJ
cuesj-252	109	8	.	.	NOUN
cuesj-252	109	9	3	3	NUM
cuesj-252	109	10	,	,	PUNCT
cuesj-252	109	11	pp	pp	ADJ
cuesj-252	109	12	.	.	PUNCT
cuesj-252	110	1	581	581	NUM
cuesj-252	110	2	-	-	SYM
cuesj-252	110	3	592	592	NUM
cuesj-252	110	4	,	,	PUNCT
cuesj-252	110	5	1976	1976	NUM
cuesj-252	110	6	.	.	PUNCT
cuesj-252	111	1	4	4	X
cuesj-252	111	2	.	.	X
cuesj-252	111	3	m.	m.	NOUN
cuesj-252	111	4	hofler	hofler	PROPN
cuesj-252	111	5	,	,	PUNCT
cuesj-252	111	6	h.	h.	PROPN
cuesj-252	111	7	pfister	pfister	PROPN
cuesj-252	111	8	,	,	PUNCT
cuesj-252	111	9	r.	r.	PROPN
cuesj-252	111	10	lieb	lieb	PROPN
cuesj-252	111	11	and	and	CCONJ
cuesj-252	111	12	h.	h.	PROPN
cuesj-252	111	13	u.	u.	PROPN
cuesj-252	111	14	wittchen	wittchen	PROPN
cuesj-252	111	15	.	.	PUNCT
cuesj-252	112	1	the	the	DET
cuesj-252	112	2	use	use	NOUN
cuesj-252	112	3	of	of	ADP
cuesj-252	112	4	weights	weight	NOUN
cuesj-252	112	5	to	to	PART
cuesj-252	112	6	account	account	VERB
cuesj-252	112	7	for	for	ADP
cuesj-252	112	8	non	non	ADJ
cuesj-252	112	9	-	-	ADJ
cuesj-252	112	10	response	response	NOUN
cuesj-252	112	11	and	and	CCONJ
cuesj-252	112	12	drop	drop	NOUN
cuesj-252	112	13	-	-	PUNCT
cuesj-252	112	14	out	out	NOUN
cuesj-252	112	15	.	.	PUNCT
cuesj-252	113	1	social	social	ADJ
cuesj-252	113	2	psychiatry	psychiatry	NOUN
cuesj-252	113	3	and	and	CCONJ
cuesj-252	113	4	psychiatric	psychiatric	ADJ
cuesj-252	113	5	epidemiology	epidemiology	NOUN
cuesj-252	113	6	,	,	PUNCT
cuesj-252	113	7	vol	vol	NOUN
cuesj-252	113	8	.	.	PROPN
cuesj-252	113	9	40	40	NUM
cuesj-252	113	10	,	,	PUNCT
cuesj-252	113	11	no	no	INTJ
cuesj-252	113	12	.	.	NOUN
cuesj-252	113	13	4	4	NUM
cuesj-252	113	14	,	,	PUNCT
cuesj-252	113	15	pp	pp	ADJ
cuesj-252	113	16	.	.	PUNCT
cuesj-252	113	17	291299	291299	NUM
cuesj-252	113	18	,	,	PUNCT
cuesj-252	113	19	2005	2005	NUM
cuesj-252	113	20	.	.	PUNCT
cuesj-252	114	1	5	5	NUM
cuesj-252	114	2	.	.	X
cuesj-252	114	3	l.	l.	PROPN
cuesj-252	114	4	lazzeroni	lazzeroni	PROPN
cuesj-252	114	5	,	,	PUNCT
cuesj-252	114	6	n.	n.	NOUN
cuesj-252	114	7	schenker	schenker	PROPN
cuesj-252	114	8	and	and	CCONJ
cuesj-252	114	9	j.	j.	PROPN
cuesj-252	114	10	taylor	taylor	PROPN
cuesj-252	114	11	.	.	PUNCT
cuesj-252	115	1	robustness	robustness	NOUN
cuesj-252	115	2	of	of	ADP
cuesj-252	115	3	multipleimputation	multipleimputation	NOUN
cuesj-252	115	4	techniques	technique	NOUN
cuesj-252	115	5	to	to	PART
cuesj-252	115	6	model	model	VERB
cuesj-252	115	7	misspecification	misspecification	NOUN
cuesj-252	115	8	.	.	PUNCT
cuesj-252	116	1	united	united	PROPN
cuesj-252	116	2	states	states	PROPN
cuesj-252	116	3	:	:	PUNCT
cuesj-252	116	4	proceedings	proceeding	NOUN
cuesj-252	116	5	of	of	ADP
cuesj-252	116	6	the	the	DET
cuesj-252	116	7	survey	survey	NOUN
cuesj-252	116	8	research	research	NOUN
cuesj-252	116	9	methods	method	NOUN
cuesj-252	116	10	section	section	NOUN
cuesj-252	116	11	,	,	PUNCT
cuesj-252	116	12	american	american	PROPN
cuesj-252	116	13	statistical	statistical	ADJ
cuesj-252	116	14	association	association	PROPN
cuesj-252	116	15	,	,	PUNCT
cuesj-252	116	16	pp	pp	PROPN
cuesj-252	116	17	.	.	PUNCT
cuesj-252	117	1	260	260	NUM
cuesj-252	117	2	-	-	SYM
cuesj-252	117	3	265	265	NUM
cuesj-252	117	4	,	,	PUNCT
cuesj-252	117	5	1990	1990	NUM
cuesj-252	117	6	.	.	PUNCT
cuesj-252	118	1	6	6	NUM
cuesj-252	118	2	.	.	X
cuesj-252	118	3	b.	b.	PROPN
cuesj-252	118	4	l.	l.	PROPN
cuesj-252	118	5	carlson	carlson	PROPN
cuesj-252	118	6	and	and	CCONJ
cuesj-252	118	7	s.	s.	PROPN
cuesj-252	118	8	williams	williams	PROPN
cuesj-252	118	9	.	.	PUNCT
cuesj-252	119	1	a	a	DET
cuesj-252	119	2	comparison	comparison	NOUN
cuesj-252	119	3	of	of	ADP
cuesj-252	119	4	two	two	NUM
cuesj-252	119	5	methods	method	NOUN
cuesj-252	119	6	to	to	PART
cuesj-252	119	7	adjust	adjust	VERB
cuesj-252	119	8	weights	weight	NOUN
cuesj-252	119	9	for	for	ADP
cuesj-252	119	10	non	non	ADJ
cuesj-252	119	11	-	-	NOUN
cuesj-252	119	12	response	response	NOUN
cuesj-252	119	13	:	:	PUNCT
cuesj-252	119	14	propensity	propensity	NOUN
cuesj-252	119	15	modeling	modeling	NOUN
cuesj-252	119	16	and	and	CCONJ
cuesj-252	119	17	weighting	weight	VERB
cuesj-252	119	18	class	class	NOUN
cuesj-252	119	19	adjustments	adjustment	NOUN
cuesj-252	119	20	.	.	PUNCT
cuesj-252	120	1	united	united	PROPN
cuesj-252	120	2	states	states	PROPN
cuesj-252	120	3	:	:	PUNCT
cuesj-252	120	4	proceedings	proceeding	NOUN
cuesj-252	120	5	of	of	ADP
cuesj-252	120	6	the	the	DET
cuesj-252	120	7	annual	annual	ADJ
cuesj-252	120	8	meeting	meeting	NOUN
cuesj-252	120	9	of	of	ADP
cuesj-252	120	10	the	the	DET
cuesj-252	120	11	american	american	PROPN
cuesj-252	120	12	statistical	statistical	PROPN
cuesj-252	120	13	association	association	PROPN
cuesj-252	120	14	,	,	PUNCT
cuesj-252	120	15	2001	2001	NUM
cuesj-252	120	16	.	.	PUNCT
cuesj-252	121	1	7	7	X
cuesj-252	121	2	.	.	X
cuesj-252	121	3	c.	c.	PROPN
cuesj-252	121	4	agostinelli	agostinelli	PROPN
cuesj-252	121	5	and	and	CCONJ
cuesj-252	121	6	l.	l.	PROPN
cuesj-252	121	7	greco	greco	PROPN
cuesj-252	121	8	.	.	PROPN
cuesj-252	122	1	weighted	weight	VERB
cuesj-252	122	2	likelihood	likelihood	NOUN
cuesj-252	122	3	in	in	ADP
cuesj-252	122	4	bayesian	bayesian	NOUN
cuesj-252	122	5	inference	inference	NOUN
cuesj-252	122	6	.	.	PUNCT
cuesj-252	123	1	new	new	PROPN
cuesj-252	123	2	york	york	PROPN
cuesj-252	123	3	:	:	PUNCT
cuesj-252	123	4	proceedings	proceeding	NOUN
cuesj-252	123	5	of	of	ADP
cuesj-252	123	6	the	the	DET
cuesj-252	123	7	46th	46th	ADJ
cuesj-252	123	8	scientific	scientific	ADJ
cuesj-252	123	9	meeting	meeting	NOUN
cuesj-252	123	10	table	table	NOUN
cuesj-252	123	11	1	1	NUM
cuesj-252	123	12	:	:	PUNCT
cuesj-252	123	13	posterior	posterior	ADJ
cuesj-252	123	14	odds	odd	NOUN
cuesj-252	123	15	ratio	ratio	NOUN
cuesj-252	123	16	and	and	CCONJ
cuesj-252	123	17	the	the	DET
cuesj-252	123	18	standard	standard	ADJ
cuesj-252	123	19	deviation	deviation	NOUN
cuesj-252	123	20	gained	gain	VERB
cuesj-252	123	21	from	from	ADP
cuesj-252	123	22	the	the	DET
cuesj-252	123	23	binary	binary	ADJ
cuesj-252	123	24	model	model	NOUN
cuesj-252	123	25	using	use	VERB
cuesj-252	123	26	variable	variable	ADJ
cuesj-252	123	27	weights	weight	NOUN
cuesj-252	123	28	estimates	estimate	NOUN
cuesj-252	123	29	of	of	ADP
cuesj-252	123	30	parameters	parameter	NOUN
cuesj-252	123	31	odds	odd	VERB
cuesj-252	123	32	ratio	ratio	NOUN
cuesj-252	123	33	sd	sd	ADP
cuesj-252	123	34	95	95	NUM
cuesj-252	123	35	%	%	NOUN
cuesj-252	123	36	credible	credible	ADJ
cuesj-252	123	37	interval	interval	NOUN
cuesj-252	123	38	constant	constant	ADJ
cuesj-252	123	39	0.54	0.54	NUM
cuesj-252	123	40	0.11	0.11	NUM
cuesj-252	123	41	0.34	0.34	NUM
cuesj-252	123	42	,	,	PUNCT
cuesj-252	123	43	0.79	0.79	NUM
cuesj-252	123	44	gestational	gestational	ADJ
cuesj-252	123	45	age	age	NOUN
cuesj-252	123	46	(	(	PUNCT
cuesj-252	123	47	centered)a	centered)a	PROPN
cuesj-252	123	48	0.79	0.79	NUM
cuesj-252	123	49	0.06	0.06	NUM
cuesj-252	123	50	0.67	0.67	NUM
cuesj-252	123	51	,	,	PUNCT
cuesj-252	123	52	0.94	0.94	NUM
cuesj-252	123	53	mother	mother	NOUN
cuesj-252	123	54	’s	’s	PART
cuesj-252	123	55	age	age	NOUN
cuesj-252	123	56	0.987	0.987	NUM
cuesj-252	123	57	0.02	0.02	NUM
cuesj-252	123	58	0.91	0.91	NUM
cuesj-252	123	59	,	,	PUNCT
cuesj-252	123	60	1.02	1.02	NUM
cuesj-252	123	61	birth	birth	NOUN
cuesj-252	123	62	weight	weight	NOUN
cuesj-252	123	63	z	z	NOUN
cuesj-252	123	64	-	-	PUNCT
cuesj-252	123	65	score	score	VERB
cuesj-252	123	66	1.05	1.05	NUM
cuesj-252	123	67	0.04	0.04	NUM
cuesj-252	123	68	0.97	0.97	NUM
cuesj-252	123	69	,	,	PUNCT
cuesj-252	123	70	1.14	1.14	NUM
cuesj-252	123	71	female	female	NOUN
cuesj-252	123	72	0.52	0.52	NUM
cuesj-252	123	73	0.18	0.18	NUM
cuesj-252	123	74	0.27	0.27	NUM
cuesj-252	123	75	,	,	PUNCT
cuesj-252	123	76	0.98	0.98	NUM
cuesj-252	123	77	agestational	agestational	ADJ
cuesj-252	123	78	age	age	NOUN
cuesj-252	123	79	centered	center	VERB
cuesj-252	123	80	around	around	ADP
cuesj-252	123	81	28	28	NUM
cuesj-252	123	82	weeks	week	NOUN
cuesj-252	124	1	kadir	kadir	PROPN
cuesj-252	124	2	:	:	PUNCT
cuesj-252	124	3	likelihood	likelihood	NOUN
cuesj-252	124	4	approach	approach	NOUN
cuesj-252	124	5	for	for	ADP
cuesj-252	124	6	bayesian	bayesian	NOUN
cuesj-252	124	7	logistic	logistic	NOUN
cuesj-252	124	8	weighted	weight	VERB
cuesj-252	124	9	model	model	NOUN
cuesj-252	124	10	12	12	NUM
cuesj-252	124	11	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-252	124	12	cuesj	cuesj	NOUN
cuesj-252	124	13	2020	2020	NUM
cuesj-252	124	14	,	,	PUNCT
cuesj-252	124	15	4	4	NUM
cuesj-252	124	16	(	(	PUNCT
cuesj-252	124	17	2	2	NUM
cuesj-252	124	18	):	):	PUNCT
cuesj-252	124	19	9	9	NUM
cuesj-252	124	20	-	-	SYM
cuesj-252	124	21	12	12	NUM
cuesj-252	124	22	of	of	ADP
cuesj-252	124	23	the	the	DET
cuesj-252	124	24	italian	italian	ADJ
cuesj-252	124	25	statistical	statistical	ADJ
cuesj-252	124	26	society	society	NOUN
cuesj-252	124	27	,	,	PUNCT
cuesj-252	124	28	2012	2012	NUM
cuesj-252	124	29	.	.	PUNCT
cuesj-252	125	1	8	8	NUM
cuesj-252	125	2	.	.	PUNCT
cuesj-252	125	3	s.	s.	PROPN
cuesj-252	125	4	r.	r.	PROPN
cuesj-252	125	5	seaman	seaman	PROPN
cuesj-252	125	6	and	and	CCONJ
cuesj-252	125	7	i.	i.	PROPN
cuesj-252	125	8	r.	r.	PROPN
cuesj-252	125	9	white	white	PROPN
cuesj-252	125	10	.	.	PUNCT
cuesj-252	126	1	review	review	NOUN
cuesj-252	126	2	of	of	ADP
cuesj-252	126	3	inverse	inverse	NOUN
cuesj-252	126	4	probability	probability	NOUN
cuesj-252	126	5	weighting	weighting	NOUN
cuesj-252	126	6	for	for	ADP
cuesj-252	126	7	dealing	deal	VERB
cuesj-252	126	8	with	with	ADP
cuesj-252	126	9	missing	miss	VERB
cuesj-252	126	10	data	datum	NOUN
cuesj-252	126	11	.	.	PUNCT
cuesj-252	127	1	statistical	statistical	ADJ
cuesj-252	127	2	methods	method	NOUN
cuesj-252	127	3	in	in	ADP
cuesj-252	127	4	medical	medical	ADJ
cuesj-252	127	5	research	research	NOUN
cuesj-252	127	6	,	,	PUNCT
cuesj-252	127	7	vol	vol	NOUN
cuesj-252	127	8	.	.	PROPN
cuesj-252	127	9	22	22	NUM
cuesj-252	127	10	,	,	PUNCT
cuesj-252	127	11	no	no	INTJ
cuesj-252	127	12	.	.	NOUN
cuesj-252	127	13	3	3	NUM
cuesj-252	127	14	,	,	PUNCT
cuesj-252	127	15	pp	pp	ADJ
cuesj-252	127	16	.	.	PUNCT
cuesj-252	128	1	278	278	NUM
cuesj-252	128	2	-	-	SYM
cuesj-252	128	3	295	295	NUM
cuesj-252	128	4	,	,	PUNCT
cuesj-252	128	5	2013	2013	NUM
cuesj-252	128	6	.	.	PUNCT
cuesj-252	129	1	9	9	NUM
cuesj-252	129	2	.	.	PUNCT
cuesj-252	129	3	s.	s.	PROPN
cuesj-252	129	4	r.	r.	PROPN
cuesj-252	129	5	seaman	seaman	PROPN
cuesj-252	129	6	,	,	PUNCT
cuesj-252	129	7	i.	i.	PROPN
cuesj-252	129	8	r.	r.	PROPN
cuesj-252	129	9	white	white	PROPN
cuesj-252	129	10	,	,	PUNCT
cuesj-252	129	11	a.	a.	PROPN
cuesj-252	129	12	j.	j.	PROPN
cuesj-252	129	13	copas	copas	PROPN
cuesj-252	129	14	and	and	CCONJ
cuesj-252	129	15	l.	l.	PROPN
cuesj-252	129	16	li	li	PROPN
cuesj-252	129	17	.	.	PUNCT
cuesj-252	129	18	combining	combine	VERB
cuesj-252	129	19	multiple	multiple	ADJ
cuesj-252	129	20	imputation	imputation	NOUN
cuesj-252	129	21	and	and	CCONJ
cuesj-252	129	22	inverse‐probability	inverse‐probability	NOUN
cuesj-252	129	23	weighting	weighting	NOUN
cuesj-252	129	24	.	.	PUNCT
cuesj-252	130	1	biometrics	biometric	NOUN
cuesj-252	130	2	,	,	PUNCT
cuesj-252	130	3	vol	vol	NOUN
cuesj-252	130	4	.	.	PROPN
cuesj-252	130	5	68	68	NUM
cuesj-252	130	6	,	,	PUNCT
cuesj-252	130	7	no	no	INTJ
cuesj-252	130	8	.	.	NOUN
cuesj-252	130	9	1	1	NUM
cuesj-252	130	10	,	,	PUNCT
cuesj-252	130	11	pp	pp	ADJ
cuesj-252	130	12	.	.	PUNCT
cuesj-252	131	1	129	129	NUM
cuesj-252	131	2	-	-	SYM
cuesj-252	131	3	137	137	NUM
cuesj-252	131	4	,	,	PUNCT
cuesj-252	131	5	2012	2012	NUM
cuesj-252	131	6	.	.	PUNCT
cuesj-252	132	1	10	10	NUM
cuesj-252	132	2	.	.	PUNCT
cuesj-252	132	3	d.	d.	PROPN
cuesj-252	132	4	clayton	clayton	PROPN
cuesj-252	132	5	,	,	PUNCT
cuesj-252	132	6	d.	d.	PROPN
cuesj-252	132	7	spiegelhalter	spiegelhalter	PROPN
cuesj-252	132	8	,	,	PUNCT
cuesj-252	132	9	g.	g.	PROPN
cuesj-252	132	10	dunn	dunn	PROPN
cuesj-252	132	11	and	and	CCONJ
cuesj-252	132	12	a.	a.	NOUN
cuesj-252	132	13	pickles	pickle	NOUN
cuesj-252	132	14	.	.	PUNCT
cuesj-252	133	1	analysis	analysis	NOUN
cuesj-252	133	2	of	of	ADP
cuesj-252	133	3	longitudinal	longitudinal	ADJ
cuesj-252	133	4	binary	binary	ADJ
cuesj-252	133	5	data	datum	NOUN
cuesj-252	133	6	from	from	ADP
cuesj-252	133	7	multiphase	multiphase	NOUN
cuesj-252	133	8	sampling	sampling	NOUN
cuesj-252	133	9	.	.	PUNCT
cuesj-252	134	1	journal	journal	NOUN
cuesj-252	134	2	of	of	ADP
cuesj-252	134	3	the	the	DET
cuesj-252	134	4	royal	royal	ADJ
cuesj-252	134	5	statistical	statistical	ADJ
cuesj-252	134	6	society	society	NOUN
cuesj-252	134	7	,	,	PUNCT
cuesj-252	134	8	vol	vol	NOUN
cuesj-252	134	9	.	.	PROPN
cuesj-252	134	10	60	60	NUM
cuesj-252	134	11	,	,	PUNCT
cuesj-252	134	12	no	no	INTJ
cuesj-252	134	13	.	.	NOUN
cuesj-252	134	14	1	1	NUM
cuesj-252	134	15	,	,	PUNCT
cuesj-252	134	16	pp	pp	ADJ
cuesj-252	134	17	.	.	PUNCT
cuesj-252	135	1	71	71	NUM
cuesj-252	135	2	-	-	SYM
cuesj-252	135	3	87	87	NUM
cuesj-252	135	4	,	,	PUNCT
cuesj-252	135	5	1998	1998	NUM
cuesj-252	135	6	.	.	PUNCT
cuesj-252	136	1	11	11	NUM
cuesj-252	136	2	.	.	PUNCT
cuesj-252	136	3	r.	r.	PROPN
cuesj-252	136	4	j.	j.	PROPN
cuesj-252	136	5	little	little	PROPN
cuesj-252	136	6	and	and	CCONJ
cuesj-252	136	7	d.	d.	PROPN
cuesj-252	136	8	b.	b.	PROPN
cuesj-252	136	9	rubin	rubin	PROPN
cuesj-252	136	10	.	.	PUNCT
cuesj-252	137	1	statistical	statistical	ADJ
cuesj-252	137	2	analysis	analysis	NOUN
cuesj-252	137	3	with	with	ADP
cuesj-252	137	4	missing	miss	VERB
cuesj-252	137	5	data	datum	NOUN
cuesj-252	137	6	.	.	PUNCT
cuesj-252	138	1	chichester	chichester	PROPN
cuesj-252	138	2	:	:	PUNCT
cuesj-252	138	3	wiley	wiley	PROPN
cuesj-252	138	4	,	,	PUNCT
cuesj-252	138	5	p.	p.	NOUN
cuesj-252	138	6	5	5	NUM
cuesj-252	138	7	,	,	PUNCT
cuesj-252	138	8	1987	1987	NUM
cuesj-252	138	9	.	.	PUNCT
cuesj-252	139	1	12	12	NUM
cuesj-252	139	2	.	.	PUNCT
cuesj-252	139	3	l.	l.	PROPN
cuesj-252	139	4	h.	h.	PROPN
cuesj-252	139	5	curtis	curtis	PROPN
cuesj-252	139	6	,	,	PUNCT
cuesj-252	139	7	b.	b.	PROPN
cuesj-252	139	8	g.	g.	PROPN
cuesj-252	139	9	hammill	hammill	PROPN
cuesj-252	139	10	,	,	PUNCT
cuesj-252	139	11	e.	e.	PROPN
cuesj-252	139	12	l.	l.	PROPN
cuesj-252	139	13	eisenstein	eisenstein	PROPN
cuesj-252	139	14	,	,	PUNCT
cuesj-252	139	15	j.	j.	PROPN
cuesj-252	139	16	m.	m.	PROPN
cuesj-252	139	17	kramer	kramer	PROPN
cuesj-252	139	18	and	and	CCONJ
cuesj-252	139	19	k.	k.	PROPN
cuesj-252	139	20	j.	j.	PROPN
cuesj-252	139	21	anstrom	anstrom	PROPN
cuesj-252	139	22	.	.	PUNCT
cuesj-252	140	1	using	use	VERB
cuesj-252	140	2	inverse	inverse	NOUN
cuesj-252	140	3	probability	probability	NOUN
cuesj-252	140	4	-	-	PUNCT
cuesj-252	140	5	weighted	weight	VERB
cuesj-252	140	6	estimators	estimator	NOUN
cuesj-252	140	7	in	in	ADP
cuesj-252	140	8	comparative	comparative	ADJ
cuesj-252	140	9	effectiveness	effectiveness	NOUN
cuesj-252	140	10	analyses	analysis	NOUN
cuesj-252	140	11	with	with	ADP
cuesj-252	140	12	observational	observational	ADJ
cuesj-252	140	13	databases	database	NOUN
cuesj-252	140	14	.	.	PUNCT
cuesj-252	141	1	medical	medical	ADJ
cuesj-252	141	2	care	care	NOUN
cuesj-252	141	3	,	,	PUNCT
cuesj-252	141	4	vol	vol	NOUN
cuesj-252	141	5	.	.	PROPN
cuesj-252	142	1	45	45	NUM
cuesj-252	142	2	,	,	PUNCT
cuesj-252	142	3	no	no	INTJ
cuesj-252	142	4	.	.	NOUN
cuesj-252	142	5	10	10	NUM
cuesj-252	142	6	,	,	PUNCT
cuesj-252	142	7	pp	pp	ADJ
cuesj-252	142	8	.	.	PUNCT
cuesj-252	143	1	s103	s103	PROPN
cuesj-252	143	2	-	-	PUNCT
cuesj-252	143	3	s107	s107	PROPN
cuesj-252	143	4	,	,	PUNCT
cuesj-252	143	5	2007	2007	NUM
cuesj-252	143	6	.	.	PUNCT