Twins Assessing Their Own and Parental Intelligence: Examining the Raters’ Agreement and the Effect of Raters’ and Targets’ Gender Research Reports Twins Assessing Their Own and Parental Intelligence: Examining the Raters’ Agreement and the Effect of Raters’ and Targets’ Gender Denis Bratko* a, Martina Pocrnić a, Ana Butković a [a] Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia. Abstract The goal of this study was to explore the raters’ agreement and the effect of raters’ and targets’ gender on self- and parental intelligence assessments in the sample of Croatian twins. Twins were asked to assess their own and their parents’ overall intelligence, as well as specific abilities from the Gardner’s theory of multiple intelligences. Data was analysed to explore: i) twins’ agreement in parental assessments and behavioural genetic analysis of the overall intelligence estimates; ii) gender differences in self- assessments; and iii) raters’ and targets’ gender effects on parental assessments. The twins’ mean correlation in their assessments of overall parental intelligence was .60. The differences between monozygotic and dizygotic twin correlations were nonsignificant for all of the estimated abilities, and model fitting analysis indicates that hypothesis about genetic effect on parental assessment of intelligence should be rejected. The hypotheses about males’ higher self-assessments for overall intelligence and for the masculine types of abilities - logical-mathematical, body-kinesthetic and spatial abilities - were confirmed. For the feminine types of abilities - verbal/linguistic, inter- and intra- personal intelligences - there were no significant gender effects. Both target and rater effect were found for the parental estimates of intelligence. Fathers were estimated higher on overall intelligence, logical-mathematical, body-kinesthetic and spatial abilities, while mothers were estimated higher on interpersonal and intrapersonal intelligence. The effect of the raters’ gender was found for overall intelligence as well as for inter- and intra- personal intelligences, where males gave higher estimates of parental intelligences than females. Keywords: self-assessed intelligence, other-assessed intelligence, Gardner’s multiple intelligences, twin study, gender Europe's Journal of Psychology, 2020, Vol. 16(2), 229–248, https://doi.org/10.5964/ejop.v16i2.1853 Received: 2018-12-13. Accepted: 2019-03-21. Published (VoR): 2020-05-29. Handling Editor: Maciej Karwowski, University of Wroclaw, Wroclaw, Poland *Corresponding author at: Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb Ivana Lučića 3, 10000 Zagreb, Croatia. E-mail: dbratko@ffzg.hr This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Intelligence is one of the central concepts in differential psychology. Numerous psychometrically validated tests were developed for assessing one's intelligence score. However, in daily life lay people often evaluate their own abilities, as well as abilities of others without using standardized measures. These self- and other- assessments of intelligence (SAI and OAI) can be detected by asking individuals to estimate their own intelligence quotient (IQ) or IQ of others on a bell curve of intelligence with a mean of 100 and a standard deviation of 15, using a deviation IQ scale as a model. Obviously, impressions about self- and other- intelligence are not only based on the actual abilities. Recent meta-analysis indicates that constructs which correlate with SAI can be categorized into four groups: i) constructs associated with intelligence; ii) tendencies and opportunities to develop intelligence; iii) constructs associated with biased self- assessments; and iv) positive states and life achievements (Howard & Cogswell, 2018). Europe's Journal of Psychology ejop.psychopen.eu | 1841-0413 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ https://ejop.psychopen.eu/ https://ejop.psychopen.eu/ https://www.psychopen.eu/ Association Between Subjectively Assessed and Measured Intelligence Although one can assume that people are able to assess their own and others’ intelligence quite precisely, studies have shown that the correlation between SAI and psychometric intelligence is usually around .30, with range between .20 and .50 (Ackerman & Wolman, 2007; Furnham, 2001). Bratko, Butkovic, Vukasovic, Chamorro-Premuzic, and von Stumm (2012) have found correlation of .33 between measured IQ and SAI in the sample of Croatian twins. Borkenau and Liebler (1993) investigated the convergence between measured and subjectively assessed IQ. They found that measured intelligence correlates .32 and .29 with self- and acquaintance ratings of intelligence, respectively. These findings indicate that SAI and OAI are not very precise and that they certainly cannot replace the validated measures of intelligence. In order to explain inaccuracy of SAI, researchers hypothesized that they may occur due to the lack of metacognitive insight or due to the broadness and the ambiguousness of the overall intelligence as a trait being evaluated (Freund & Kasten, 2012). The similar reasoning regarding broadness and ambiguousness of the intelligence concept might be extrapolated to OAI as well. The Realistic Accuracy model borrowed from personality judgments (Funder, 1995; see also Connelly & Ones, 2010) describes accuracy as a function of the availability, detection, and utilization of relevant behavioral cues, and recognition of these cues might be relevant for the accurracy in assessing abilities of other people as well. The Twin Studies of Subjectively Assessed Intelligence Classical twin study compares phenotypic resemblances of monozygotic (MZ) twins who are genetically identi- cal and dyzgotic (DZ) twins who share half of their genes on average in order to estimate the extent to which genetic variation contributes to the phenotypic variation of the trait. Meta-analysis of twin correlations and reported variance components for 17,804 traits showed that the heritability estimate across all traits is 49% (Polderman et al., 2015). There are only a few twin studies of SAI and they have shown that heritability of self-assessed abilities is as high as for measured intelligence. Spinath, Spinath, and Plomin (2008) reported genetic influences of 40%, Greven, Harlaar, Kovas, Chamorro-Premuzic, and Plomin (2009) reported heritabili- ty of 51%, while Bratko et al. (2012) reported heritability of 57%. On the other hand, as far as we know, there are no prior twin studies, which include OAI. Twin design in estimating parental intelligence can also allow, besides testing the hypothesis about genetic and environmental influence, the investigation of rater agreement in OAI. We know little about the agreement of family members in their estimation of abilities of other family member. For example, in a broad personality domain, the meta-analysis (Connelly & Ones, 2010) yielded rater- rater correlations of two family members estimating other family member traits of .37, .45, .38, .25, and .36 for Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness, respectively. Although we are not aware of such family rater-rater agreement studies of OAI, Borkenau and Liebler (1993) reported average correlation of .52 between self- and close acquientance intelligence estimate. The Hubris-Humility Effect Even though SAI and OAI are not fully correspondent with psychometrically measured intelligence, these estimates are interesting research topic because they can provide important information about the lay views of intelligence. In general, studies have shown that people are likely to overestimate their intelligence score and see themselves as above the average. However, there is a difference between men and women in that trend. Namely, men usually provide statistically higher estimations than women do. That was firstly stated in Twins' Assessing Their Own and Parental IQ 230 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ Hogan's (1978) pioneer study of intelligence estimation where he reported that in half of his 11 studies the difference between male and female intelligence self-estimations was statistically significant. Since then, there have been a number of studies worldwide confirming that trend (e.g. Beloff, 1992; Bennett, 1996, 1997, 2000; Furnham & Chamorro-Premuzic, 2005; Furnham, Kosari, & Swami, 2012; Furnham & Storek, 2017; Neto, Furnham, & da Conceição Pinto, 2009; Kang & Furnham, 2016; Rammstedt & Rammsayer, 2000; von Stumm, Chamorro-Premuzic, & Furnham, 2009). This gender difference in intelligence self-estimation is considered consistent and culturally invariant and is known as hubris-humility effect (Furnham, Hosoe, & Tang, 2001). Besides self-estimations of overall intelligence, many studies investigated gender differences in specific do- mains, mostly using Gardner's (1983, 1999) theory of multiple intelligences. Gardner (1983) initially suggested that every individual should develop to some extent seven different types of intelligence. He defined ''object-re- lated'' forms that include logical-mathematical, spatial and body-kinesthetic intelligence. The ''object-free'' forms consist of verbal/linguistic and musical intelligence. Finally, there are two types of personal intelligence, inter- personal and intrapersonal domains. Lately, Gardner (1999) defined three new possible types – naturalistic, spiritual, and existential intelligence, but concluding that only naturalistic intelligence merits addition to seven original types. Although Gardner’s theory is not a psychometrically validated theory of the intelligence structure, and Gardner has not designed instrument for measuring his different types of intelligence, it has been exten- sively used in the study of SAI. The reason for this was that this theory offered a more fine-grained analysis of the differences in lay self-estimates, and not because the idea was to validate or support the theory itself (Furnham, 2001). In addition, Gardner’s view of intelligence is very appealing to lay people due to its view that everyone can be high in some type of intelligence. Studies that investigated self-estimations of these multiple intelligences showed that the biggest and most consistent differences between men's and women's self-estimates were found in mathematical/logical and spatial intelligence, with men providing higher scores. Similar pattern was also found in the studies that used psychometric Cattell-Horn-Carroll theory of intelligence (Ortiz, 2015) with men giving higher scores than women in estimating their overall intelligence and the most of broad abilities (Furnham & Mansi, 2014; Kang & Furnham, 2016). A meta-analytic study by Syzmanowicz and Furnham (2011) found the highest effect-size, with males assessing themselves higher than females, for mathematical/logical (d = .44), followed by spatial (d = .43) and overall (d = .37) intelligence, while the smallest effect size was in verbal/linguistic (d = .07) SAI where females provided higher estimates. Gender Effect in Intelligence Assessment of Others Although most of the studies focused on the people's belief about their own intelligence, some of them also showed that these gender differences were not limited to SAI. Studies of OAI indicate that there is a noticeable trend where people see their fathers, grandparents or sons as more intelligent than their mothers, sisters and daughters (Furnham, 2000; Furnham & Chamorro-Premuzic, 2005; Furnham & Gasson, 1998; Furnham et al., 2001; Neto & Furnham, 2011). Given that the focus of this study, besides gender differences in SAI, are gender differences in OAI or, more specifically, the parental estimates, we will also review the findings in that field. In his pioneer study, Hogan (1978) also reported that both male and female students attributed higher IQ scores to their fathers than to their mothers. That was followed by Beloff's (1992) finding that women believe they are intellectually equal to their mothers, but inferior to their fathers, while men saw themselves as equal to their fathers and superior to their mothers. Since then, there have been several studies in different cultures showing that people tend to give higher overall intelligence scores to their fathers than to their mothers (e.g. Furnham & Chamorro-Premuzic, 2005; Furnham & Wu, 2008; Furnham et al., 2012; Petrides, Furnham, & Martin, Bratko, Pocrnić, & Butković 231 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ 2004; Swami, Furnham, & Zilkha, 2009). Along with overall intelligence, studies also focused on perceived differences in parents' multiple intelligences. As well as with self-estimations, the most consistent finding is that fathers are believed to be more intelligent in mathematical/logical and spatial domains (Furnham & Wu, 2008; Ortner, Müller, & Garcia-Retamero, 2011; Swami et al., 2009). On the other hand, mothers are often given higher scores on interpersonal, intrapersonal and musical intelligence (Bennett, 1996; Ortner et al., 2011; Rammstedt & Rammsayer, 2000). These findings indicate division of masculine and feminine types of abilities. Bennett (2000) reported that people perceive mathematical, spatial and body-kinesthetic intelligences as more masculine, while personal, musical, and verbal/linguistic intelligences are perceived as abilities that are more feminine. Interestingly, in some studies fathers were given higher estimates in verbal factor (Furnham et al., 2012; Rammstedt & Rammsayer, 2000; Swami et al., 2009), although it is usually considered as type of ability where women excel. In addition, Furnham (2000) suggests that people primarily relate IQ to mathematical and spatial domains and see them as essence of intelligence. Therefore, it can be said that people see intelligence as male-normative. Indeed, studies have shown that the best predictors of estimated overall intelligence are numerical and spatial domains (Furnham, 2001; Furnham et al., 2012; Neto & Furnham, 2011; Swami et al., 2009). This illustrates that people do not have a broad view on intelligence that includes all domains suggested by Gardner, but that they are mostly focused on masculine types of abilities when considering overall intelligence. Sources of Gender Differences There are two different hypotheses that have been discussed in order to explain gender differences in esti- mated intelligence. First one argues that gender differences in estimations reflect small but real differences in intelligence between men and women which people tend to overestimate. Thus, people estimate men as more intelligent because they observe that pattern in daily lives (Furnham & Rawles, 1995). However, results are inconclusive because gender differences in overall intelligence have been found in both the direction of higher men’s and higher women’s scores (e.g. Daseking, Petermann, & Waldmann, 2017; Irwing, 2012; Keith, Reynolds, Patel, & Ridley, 2008; Reynolds, Keith, Ridley, & Patel, 2008; van der Linden, Dunkel, & Madison, 2017), while some research shows that there are negligible gender differences in overall intelligence (e.g. Camarata & Woodcock, 2006; Flynn & Rossi-Casé, 2011; Halpern, 2012; Savage-McGlynn, 2012; Sternberg, 2014). Psychometric differences are usually found in the mathematical/logical and spatial domain where men have higher results (Hyde, Fennema, & Lamon, 1990; Voyer, Voyer, & Bryden, 1995), which is in line with gender differences in multiple intelligence estimations. The second hypothesis states that gender differences can primarily be attributed to gender stereotypes (Rammstedt & Rammsayer, 2000). When it comes to parental estimations, judgments about their IQ score could also be associated with mothers' and fathers' family roles, work status or other additional cues which raters might use. Ortner et al. (2011) showed that estimation of parents' overall intelligence can be predicted by their education and current employment status and argue that being unemployed or working part-time is more related to feminine gender role, while full-time employment is mostly perceived in relation to the male gender role and thus the higher estimations of intelligence. Twins' Assessing Their Own and Parental IQ 232 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ Rater Effect Another phenomenon in OAI are possible differences in estimates between male and female raters. Thus, the question is does hubris-humility effect extend to estimates of the others – both male and female targets? If males tend to give themselves higher estimations than females do, does that mean they are also more prone to give higher estimates to all others? Certain studies have confirmed that assumption. For example, in Swami et al. (2009) study males rated both of their parents as having higher intelligence for most intelligence types than did females, and Furnham et al. (2001) reported that male participants rated fathers as overall more intelligent than did female participants. In Furnham, Arteche, Chamorro-Premuzic, Keser, and Swami (2009) study, males also rated their fathers, but not their mothers as having higher scores for most intelligence types than did females. Yuen and Furnham (2006) reported higher male's estimates than those given by females, for several fathers' intelligence types and for mothers' spiritual intelligence. However, Furnham, Rakow, Sarmany-Schuller, and De Fruyt (1999) found out that Belgian males rated their fathers' overall IQ higher than Belgium females, but the opposite pattern appeared in a sample of Slovakian students. In addition, in Furnham and Wu (2008) study, gender differences occured for fathers' spatial and intrapersonal intelligence where females ascribed higher estimates than did male students. These findings indicate that raters’ gender may influence estimates of others, but its role and direction must be further explored and clarified. The Present Study The goal of this study was to examine: i) twins’ agreement in their assessments of parental intelligence and behavioural genetic analysis of those ability estimates; ii) gender differences in SAI; and iii) raters’ and targets’ gender effects on parental assessments of intelligence. As far as we know, none of the previous studies of parental intelligence estimates have included two raters from the same family and this is the first study of parents' intelligence estimation where sample consists of twin pairs. Due to this specific sample, we could investigate the rater-rater agreement of parental intelligence estimations by examining twins’ correlations in judgement of their parents' IQ scores. Since rater-rater agree- ment in judging the target traits depends on the level of knowing the targets and on the availability of the relevant cues which might be used for the accurate estimate of the trait (Funder, 1995), we expect substantial correlations between twins. Additionaly, by comparing MZ and DZ similarity and testing the behavioural genetic models, we could explore the aethiology of individual differences in impressions about the targets’ intelligence. Estimates of the genetic and environmental contribution to the individual differences in SAI based on this sample is published elsewhere (Bratko et al., 2012) and the result of that study suggests a substantial genetic effect. However, individual differences in twin assessments of parental traits reflect their impressions and, since both raters are rating the same target, the differences in similarity between MZ and DZ twins are not expected. Therefore, we expect that behavioural genetic model fitting of parental intelligence estimates would, in addition to always present non-shared environmental influence (E), reflect shared environmental influence (C) which primarily comes from the exposure to the target’s behaviour and from the availability of the relevant cues which are used to estimate parental intelligence. The second goal of this study was to extend previous findings on gender differences in self-assessed overall and domain specific intelligences to a new culture. To date, there have been numerous studies in countries all over the world, e.g. in Argentina (Furnham & Chamorro-Premuzic, 2005), South Korea (Kang & Furnham, Bratko, Pocrnić, & Butković 233 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ 2016), Egypt (Furnham & Mottabu, 2004), Iran (Furnham et al., 2012), Russia (Furnham & Shagabutdinova, 2012), Britain and Turkey (Furnham et al., 2009), etc. Most of these studies confirmed hubris-humility effect in SAI and showed that men perceive themselves higher on overall intelligence than women. Gender differences were also found in specific abilities, mostly on spatial and logical-mathematical where men provided higher estimates, while there was a tendency for women to have higher estimates on verbal/linguistic and personal intelligences, perceived as abilities that are more feminine. Although several studies included participants from European countries, none of them investigated gender differences in intelligence estimation on the Croatian sample. Thus, our next hypothesis is that man will have higher estimates than women on overall intelligence, as well as on more masculine abilities (spatial, logical-mathematical and body-kinesthetic intelligence), while women will have higher self-estimated scores on more feminine abilities (inter- and intra- personal, verbal/lin- guistic and musical intelligence). In addition, using available data on twins’ measured intelligence and personal- ity, we expect that gender effect in SAI would not change when these variables are controlled for. Along with gender differences in SAI, we were further interested in testing gender effect in twin estimations of parental intelligence, that is whether our participants would give higher intelligence scores to their mothers or to their fathers. Previous studies mostly showed that fathers are perceived as more overall intelligent than mothers. As with self-estimations, there is also an evident distinction between more masculine and feminine abilities in parental estimations. Fathers are perceived as more intelligent in the spatial and logical-mathemat- ical domain, while mothers are seen more intelligent in the personal and musical domain. This pattern of result was confirmed in various countries, such as Argentina (Furnham & Chamorro-Premuzic, 2005), Iran (Furnham et al., 2012), Britain and France (Swami, Furnham, & Zilkha, 2009), etc. In accordance with those findings, we hypothesize that Croatian participants will give higher overall intelligence scores to their fathers than to their mothers and that fathers will be given higher scores on masculine types of abilities (spatial, logical-mathematical and body-kinesthetic intelligence), while mothers will be given higher scores on feminine types of abilities (personal, verbal/linguistic and musical intelligence). Finally, we are aiming to investigate the effect of raters’ gender on parental estimates of intelligence by examining whether male and female participants differ in size of IQ scores given to their parents. As stated earlier, although the results from previous studies were inconsistent, some of them showed that men tend to give higher scores than women on overall and some specific intelligence types when estimating others (e.g. Swami et al., 2009, Furnham et al., 2001). Along with those findings, our final hypothesis was that there will be an effect of rater’s gender in a way that male participants will tend to give higher intelligence scores to their parents than female participants. For the interaction effect we did not have any specific expectations. Due to the multiple testing, we set the risk level for the acceptance of all hypotheses to one percent. Method Participants Participants in the study were twins from the Zagreb area. The initial sample was formed in 2007 based on the register of citizens from which twin pairs born between 1985 and 1992 were identified. In total 2005 individuals were contacted and 732 (36.5%) returned filled in questionnaires via mail. From those individuals, 518 had data on self-assessed intelligence (79 MZ twin pairs, 83 DZS twin pairs, 82 DZO twin pairs and 30 twins without Twins' Assessing Their Own and Parental IQ 234 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ co-twin participating) and 483 participants had valid data of parents’ intelligence estimations. There were 220 male and 298 female participants, and their age varied between 15 and 22 years (M = 18.77, SD = 2.28). Measures and Procedure Zygosity Zygosity was determined with an 11-items questionnaire evaluating physical similarities (e.g. facial appearance, hair colour) and twin confusion by parents, other family members, teachers, casual friends and strangers. The use of questionnaires for zygosity determination has been shown to be accurate around 95% in different populations and cohorts (e.g. Torgersen, 1979; Reed et al., 2005; Song et al., 2010). Self-Assessed Intelligence We used a standard procedure to measure self-assessed intelligence. On one page a normal distribution was shown with a mean of 100 and distribution of six standard deviations (–3 to +3) together with brief descriptions of the anchor scores (e.g., 55 “mild retardation,” 100 “average,” 145 “gifted”). Below the distribution a grid with 11 rows and four columns was shown. In rows short descriptions were provided for overall intelligence and 10 multiple intelligences (verbal/linguistic, logical-mathematical, musical, body-kinesthetic, spatial, interpersonal, intrapersonal, naturalist, spiritual, and existential) taken from Gardner (1999). After reading these descriptions, participants were asked to write in columns estimates of their own, their mothers’ and their fathers’ intelli- gence. Self- and parental estimates for overall intelligence and eight multiple intelligences (verbal/linguistic, logical-mathematical, musical, body-kinesthetic, spatial, interpersonal, intrapersonal, and naturalistic intelligen- ces) according to the Gardner’s (2006) theory were used in this study. Measured Intelligence and Personality Since SAI may partly reflect individual differences in real (measured) psychometric intelligence and personality, we have used these measures as control variables when testing the gender effect on overall SAI. Intelligence was assessed by the 20- itmes Croatian adaptation of a synononyms/antonyms subtest of General Aptitude Test Battery (Tarbuk, 1977) which is, according to the test manual, highly saturated with g factor. Personality traits were measured with Croatian adaptation of NEO-Five Factor Inventory (Costa & McCrae, 1992). The Cronbach's α coefficients were .81, .72, .57, .66, and .81 for Neuroticism, Extraversion, Openness, Agreeable- ness, and Conscientiousness, respectively. Results Rater Agreement and Behavioural Genetic Analysis of Parental Estimates of Intelligence Due to the specific composition of our sample, we were able to examine if there is rater agreement for parental estimates of intelligence. We calculated twin intraclass correlations for intelligence estimates of mothers and fathers. As can be seen from Table 1, there is a significant agreement between twins in their ratings of both their fathers’ and mothers’ intelligences. Correlations range from .30 to .64 for fathers’ estimates, and .29 to .59 for mothers’ ability estimates. Rater agreement for both fathers’ and mothers’ estimates of intelligence is highest (all rs > .50) for overall intelligence, verbal/linguistic intelligence, logical-mathematical intelligence and Bratko, Pocrnić, & Butković 235 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ interpersonal intelligence. The correlations of parental intelligence estimates were similar for MZ and DZ twins. The average correlations of MZ and DZ twins for estimation of overall parental intelligence was .63 and .56, respectively. 99% confidence interval around MZ and DZ twin correlations overlap indicating that there are no statistical differences between them. The twin agreement for fathers and mothers overall IQ estimate was .63 and .54, respectively, while the median estimate for eight Gardner’s specific abilities was .49, confirming the second set of hypotheses regarding substatial rater-rater agreement of parental estimates of intelligence. The average overall correlation of parental intelligence estimates across all twin pairs and both parents was .60i. In addition, we ran genetic analyses on parental overall intelligence estimates in the statistical program Mx (Neale, Boker, Xie, & Maes, 2006; Neale & Maes, 2004). After assumption testing, univariate models were fitted in order to estimate A (additive genetic), C (common environmental) and E (unique environmental) influences, and then nested reduced univariate models (AE, CE and E) were compared to the full models in order to test which parameters were significant. For both fathers and mothers, confidence interval for the genetic influences (A) in the full model included zero and therefore A parameter could be dropped from the model. The best fitting model for both fathers’ and mothers’ intelligence estimates was a CE model with common environment (C) accounting for 63% and 51% of the variance, respectively. Table 1 Twin Intraclass Correlations Ability Fathers as target Mothers as target Fathers as target Mothers as target All twins raters All twins raters MZ twins raters DZ twins raters MZ twins raters DZ twins raters Overall IQ .64 (.53-.73) .54 (.42-.65) .65 (.43-.79) .64 (.50-.75) .61 (.39-.76) .51 (.35-.64) Verbal/Linguistic .57 (.44-.67) .59 (.47-.69) .69 (.49-.82) .52 (.36-.66) .57 (.34-.74) .60 (.45-.71) Logical-mathematical .62 (.51-.72) .56 (.44-.66) .53 (.28-.72) .65 (.51-.75) .72 (.55-.84) .48 (.31-.62) Musical .42 (.27-.55) .50 (.37-.61) .41 (.13-.63) .43 (.24-.58) .60 (.37-.75) .46 (.28-.60) Body-kinesthetic .31 (.15-.46) .30 (.15-.45) .37 (.09-.60) .29 (.09-.47) .50 (.25-.69) .22 (.02-.40) Spatial .45 (.31-.58) .42 (.27-.55) .49 (.23-.69) .44 (.25-.59) .49 (.23-.68) .38 (.20-.54) Interpersonal .62 (.49-.71) .53 (.39-.64) .69 (.48-.82) .60 (.45-.72) .53 (.28-.71) .52 (.36-.66) Intrapersonal .49 (.35-.61) .42 (.27-.54) .51 (.26-.70) .48 (.30-.62) .54 (.30-.72) .37 (.18-.53) Naturalistic .30 (.13-.45) .29 (.14-.44) .41 (.13-.63) .24 (.04-.43) .49 (.23-.68) .21 (.01-.39) n of pairs 228 242 73 155 78 164 Note. With 99% Confidence Intervals in parentheses. Gender Differences in Self-Assessed Intelligence In order to examine if men and women differ in their self-assessed intelligence, we calculated a series of t-tests for independent samples. Since our sample consisted of twin pairs, we corrected the degrees of freedom associated with t-test values to half, so that the degrees of freedom associated with the calculated t-test values were 258 instead of 516, reflecting the number of pairs rather than number of individual participants (see McGue, Bacon, & Lykken, 1993 for detail explanation of that procedure). Also, Levene’s test for equality of variances was found to be violated for overall intelligence, F(1, 516) = 21.92, p < .001, logical-mathematical intelligence, F(1, 516) = 10.81, p = .001, and spatial intelligence, F(1, 516) = 8.34, p = .004). Owing to these violated assumptions, the t-statistic not assuming homogeneity of variance was computed for those intelligen- ces. Results are presented in Table 2. Twins' Assessing Their Own and Parental IQ 236 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ Table 2 Descriptive Statistics and Mean Differences in Self-Assessed Intelligence Between Males (n = 220) and Females (n = 298) Intelligence Males Females t df dM SD M SD Overall IQ 108.99 12.72 105.17 9.54 3.74* 194.59 .34 Verbal/Linguistic 103.23 12.72 104.40 10.97 -1.12 258 -.10 Logical-mathematical 105.26 14.69 100.93 13.04 3.48* 219.22 .31 Musical 102.20 16.82 102.43 15.64 -0.16 258 -.01 Body-kinesthetic 114.54 16.29 108.41 14.85 4.46* 258 .39 Spatial 111.47 15.18 104.62 12.87 5.41* 212.40 .49 Interpersonal 110.51 13.53 111.77 12.86 -1.08 258 -.10 Intrapersonal 109.33 13.55 108.11 13.71 1.00 258 .09 Naturalistic 102.83 11.72 102.25 11.31 0.57 258 .05 *p < .01. The results of statistical testing confirmed the hypothesis that male participants would have higher means on self- assessed overall intelligence and masculine abilities, namely logical-mathematical, body-kinesthetic, and spatial abilities. However, the hypothesis that females would have higher means on feminine abilities, namely inter- and intra- personal, verbal/linguistic, and musical intelligence was not confirmed. Point-biserial correlation of the gender (male coded as 1) with the measured intelligence, Neuroticism, Extra- version, Openness, Agreeableness, and Conscientiousness were, respectively, .11, .29, .00, .07, .05, and .07. (p < .001 for Neuroticism, all other rs non significant). We calculated the correlation between gender and SAI before and after controlling for measured IQ and personality traits. These correlations were the same. To be more specific correlation between gender and self-estimated intelligence was r(518) = -.17, p < .001, while the partial correlation after controlling for measured IQ and personality traits was r(492) = -.17, p < .001. Effect of Raters’ and Targets’ Gender in Parental Estimates of Intelligence In order to examine if people give higher estimates of intelligence to their fathers than to their mothers and if there are effects of raters’ gender on parental estimates of intelligence, we ran a series of analysis of variance. We tested the main effects of parents’ gender and raters’ gender on parental estimates of intelligence, as well as the interaction between parents’ and raters’ gender. Descriptive statistics for estimations of fathers’ and mothers’ intelligences, as well as for male and female raters separately, are presented in Table 3, and the results of the analyses of variance are presented in Table 4. None of the interactions was statistically significant. For the offspring estimates of parental overall intelligence, logical-mathematical intelligence, body-kinesthetic intelligence and spatial intelligence we found main effects of parents’ gender - fathers were given higher intelligence scores than mothers – mirroring the findings on self-estimates and supporting the gender effects on overall and masculine types of intelligence. Mothers were given the higher estimates for interpersonal and intrapersonal intelligence, so the set of hypotheses regarding feminine types of intelligence was partially confirmed. Significant effect of the raters’ gender was found for the estimates of parental overall intelligence, F(1, 481) = 10.31, p = .001, ηp2 = .02, interpersonal intelligence, F(1, 481) = 7.10, p = .008, ηp2 = .02, and intrapersonal intelligence, F(1, 481) = 8.11, p = .005, ηp2 = .02, with females Bratko, Pocrnić, & Butković 237 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ giving lower parental estimates than males. These findings partially confirmed the hypotheses about raters’ effects. Table 3 Descriptive Statistics in Parental Estimates of Intelligence Intelligence Male raters Female raters Total Fathers as target Mothers as target Fathers as target Mothers as target Fathers as target Mothers as target M SD M SD M SD M SD M SD M SD Overall IQ 111.58 13.25 108.69 11.17 108.19 11.93 105.87 10.81 109.62 12.60 107.05 11.04 Verbal/Linguistic 108.64 14.18 108.78 13.60 105.79 14.02 108.82 12.61 106.99 14.14 108.81 13.02 Logical-mathematical 110.39 15.83 102.88 12.75 109.74 14.50 102.72 12.36 110.01 15.06 102.79 12.51 Musical 100.03 13.86 101.18 11.89 99.72 13.61 99.02 13.22 99.85 13.70 99.93 12.71 Body-kinesthetic 106.45 14.65 100.15 12.81 105.69 12.57 100.36 11.64 106.01 13.47 100.27 12.13 Spatial 113.15 14.27 105.07 13.39 110.84 13.95 103.48 12.57 111.81 14.11 104.15 12.93 Interpersonal 105.82 15.25 112.26 13.51 103.35 14.13 108.98 14.01 104.39 14.65 110.36 13.88 Intrapersonal 108.87 13.35 109.44 13.12 104.59 13.39 107.45 13.01 106.39 13.52 108.29 13.08 Naturalistic 105.09 11.87 104.59 11.07 104.28 12.51 104.51 10.94 104.62 12.24 104.54 10.98 n of pairs 203 203 203 203 280 280 280 280 483 483 483 483 Table 4 Results of Analysis of Variance for Gender and Rater Effect in Parental Estimates of Intelligence (N = 483) Intelligence Targets’ gender (F) Effect size (ηp2) Raters’ gender (F) Effect size (ηp2) Targets x Raters (F) Effect size (ηp2) Overall IQ 28.17* .06 10.31* .02 0.33 .00 Verbal/linguistic 5.68 .01 1.77 .00 4.71 .01 Logical-mathematical 92.09* .16 0.16 .00 0.10 .00 Musical 0.11 .00 1.51 .00 1.83 .00 Body-kinesthetic 87.95* .16 0.08 .00 0.61 .00 Spatial 109.52* .19 3.78 .01 0.25 .00 Interpersonal 65.37* .12 7.10* .02 0.30 .00 Intrapersonal 10.84* .02 8.11* .02 4.82 .01 Naturalistic 0.07 .00 0.22 .00 0.51 .00 Note. F = F test for the effect of gender of a parents (targets), twins (raters) or targets x raters interaction; ηp2 = partial eta squared for the effect size. *p < .01. Discussion The goal of this study was to explore the raters’ agreement and the effect of raters’ and targets’ gender on self- and parental intelligence assessments in the sample of Croatian twins. This is the first twin study of parental intelligence assessment, and additionally, to our knowledge, the first study that uses more than one rater from the same family assessing intelligence of the other family member. Twins' Assessing Their Own and Parental IQ 238 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ Twin Agreement and Behavioural Genetic Analysis of Parental Estimates of Intelligence First aim of this study refers to participants’ estimations of their parents' score on overall and eight Gardner’s intelligences. Due to our specific sample that consists of twin pairs, we had two raters from the same family, i.e. two independent intelligence estimates for mothers and fathers. Therefore, we were interested in investigating consensus between raters in estimation of their mothers’ and fathers’ intelligence scores. Results showed that all twin intraclass correlations were substantial. The twin correlation was .60 for the overall IQ estimate, and for the eight multiple intelligence estimates the median correlation was .49. The twin agreement for the parental overall intelligence estimate was higher than meta-analyzed mean correlation of two raters from the same family who judged Five-facor personality traits which ranged from .25 to .45 (Connelly & Ones, 2010), and higher than typical correlations between self- and other- intelligence assessments with measured intelligence (Ackerman & Wolman, 2007; Borkenau & Liebler, 1993; Bratko et al., 2012; Furnham, 2001), which are in the neigborhood of .30. However, obtained twin agreement was only slightly higher than correlation between self- and close acquaintance intelligence assessment (Borkenau & Liebler, 1993). Higher correlations between two impressions (self- rater or rater-rater assessments) than self- or rater- correlations with measured intelligence sugest that both SAI and OAI are, besides measured intelligence, based on the additional cues beyond pure behavioural expression of the ability. Similar twin correlations were found for both mothers’ and fathers’ intelligence estimates. However, the lowest agreement between raters was found for naturalistic (rs = .30 for fathers; rs = .29 for mothers) and body kinesthetic (rs = 31. for fathers; rs = .30 for mothers) intelligences, which may reflect the lower validity of these concepts from the Gardner multiple intelligence theory. On the other hand, the highest agreement was found for overall, logical-mathematical, interpersonal and verbal/linguistic intelligences. It can be assumed that the descriptions of those intelligence types were easier to understand and that raters had similar idea about their meaning. Furthermore, since the highest consensus was found for overall intelligence, it seems that raters were having a similar definition and view of what general intelligence is. Since to our knowledge there are no twin studies of OAI, we also used the specific compostion of our sample to examine genetic and environmental influences to individual differences in OAI. MZ and DZ correlations for both mothers’ and fathers’ overall intelligence scores were similar and model fitting has indicated that individual differences in OAI can be contributed to common and unique environmental influences. This is different from the usual pattern where genetic factors play an important role in explaining individual differences in a trait. However, substantial effect of the common environment indicates that twin judgments of parental intelligence are not genetically mediated and are guided by the cues, which come from the exposure to the same environment. Gender Differences in Self-Assessed Intelligence The second goal of this study was to extend the existing findings on gender differences in assessing own intelligence to a new culture and with a specific twin sample. Most of the obtained results confirmed our hypotheses showing that the universal pattern of gender differences in SAI can also be found in a Croatian sample. We wanted to investigate if male and female participants differ in self-assessed overall IQ and eight domains of intelligence defined by Gardner (2006). In accordance with the most of previous studies in the area, gender differences in SAI were found for overall intelligence, logical-mathematical intelligence, body-kinesthetic intelligence and spatial intelligence, with males reporting higher SAI scores on these domains compared to fe- Bratko, Pocrnić, & Butković 239 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ males. This is completely in line with our hypothesis that men will have higher estimates than women on overall intelligence, as well as on those abilities that are usually perceived as more masculine. The biggest effect was found for spatial intelligence (d = .49), very similar to the effect size (d = .43) reported in a meta-analytic study of gender differences in SAI by Syzmanowicz and Furnham (2011). Since findings support that there are real differences between men and women in spatial ability (e.g. Voyer et al., 1995), we can assume that gender difference in SAI on spatial domain reflects this difference that really exists between genders. On the other hand, females have not perceived themselves significantly higher than males in any intelligence domain. We have not found gender differences in either personal, musical or verbal ability, as hypothesized since those domains are stereotypical perceived as more feminine. However, in some of the studies female participants also did not provide significantly higher results in any intelligence domain (e.g. Furnham & Chamorro-Premuzic, 2005; Furnham & Wu, 2008; Kang & Furnham, 2016), including the study in Poland (Furnham, Wytykowska, & Petrides, 2005). Therefore, we can say our results indicate existence of hubris-humility effect in a Croatian sample, where male participants are prone to give themselves higher IQ scores than females on overall and few specific abilities, while female participants do not have that pattern in any intelligence domain. In addition, our results are in line with the hypothesis that culture plays a role in hubris-humility effect. Storek (2011) found that the effect size (η2 = .08) for mathematical and spatial intelligence or domain-masculine IQ was in Czech Republic smaller than in 6 UK samples (η2 range = .17-.32). In our study effect size for mathematical intelligence was η2 = .05, and for spatial intelligence η2 = .13. However, it is important to point out that both males’ and females’ average scores on overall as well as on each of eight types of intelligence is above the population theoretical mean score of 100. That is in line with findings that people generally have a tendency to overestimate their abilities, known as ''lake Wobegon'' effect (Kruger, 1999). In our study, males gave themselves the highest estimates on body-kinesthetic intelligence (M = 114.54, SD = 16.29), while females scores were highest on interpersonal intelligence (M = 111.77, SD = 12.86). Effect of Raters’ and Targets’ Gender in Parental Estimates of Intelligence Besides participants’ agreement in their judgment of parents’ intelligence, we wanted to investigate the effect of both raters’ and targets’ gender in the assessment on parental intelligence estimation. We have found main effects for parents’ gender and raters’ gender in parental estimation but no interaction effects. Results of the main effects of parental gender were in line with our hypothesis. Fathers were estimated as more intelligent than mothers on same domains where male participants provided higher SAI scores - on overall intelligence, logical-mathematical intelligence, body-kinesthetic intelligence and spatial intelligence. On the other hand, on interpersonal intelligence and intrapersonal intelligence participants gave higher intelligence scores to mothers than to fathers. The biggest effect was found for spatial intelligence (ηp2 = .19) followed by logical-mathematical and body-kinesthetic intelligence (ηp2 = .16). These results are correspondent with Bennett's (2000) idea that different intelligence types can be divided into two factors – masculine and feminine abilities, and it seems that those stereotypic views are present among Croatian participants. However, our hypothesis was not fully confirmed because mothers were not perceived as more intelligent in verbal/linguistic or in musical domain. Despite the fact that verbal intelligence is traditionally seen as a female type of ability, it is interesting that gender difference in parental estimation of that domain was not found in some of the other studies as well, and in some of them fathers were given even higher scores (Furnham et al., 2012; Rammstedt & Rammsayer, 2000; Swami et al., 2009). The crucial question is why gender differenes in estimates of parental intelligence Twins' Assessing Their Own and Parental IQ 240 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ exist? If the assumption that OAI depends on additional cues, besides real gender differences in ability, is correct, then we can ask ourselves which cues judges use when they assess parental intelligence. One possible cue to higher intelligence of fathers than mothers could be the divison of housework and family decision making. Research has shown that women are still responsible for about two thirds of routine house- work (Bartley, Blanton, & Gilliard, 2005; Bartolac & Kamenov, 2013; Lachance-Grzela & Bouchard, 2010). Davis (2010) points that one of the main reasons why women do more housework than men is that they have less power. Furthermore, individual with more power in the relationship makes more decisions in that relationship (Fox & Murry, 2000). An interesting study by Zipp, Prohaska, and Bemiller (2004) tested if the asymmetry between husbands and wives on decision making, the division of household labor, child care, and so forth can be explained, in part, by taking into account the invisible power of men. Results showed that wives were much more likely than husbands to agree with their spouses’ known answers, and that tendency was virtually unaffected by women’s financial, cultural, and political capital. The other possible cue to higher intelligence of fathers than mothers could be related to working positions and earnings. Recent gender gap report (World Economic Forum, 2018) has shown that there are more women than men in education and health industry, while the largest industry gender gaps were found for manufacturing, energy and mining, and software and IT services industry with more men than women. In addition, it was found that male professionals are found in positions that are generally more lucrative and of a more senior level. In line with that, income gaps are particularly persistent, not only in pay, but also in division of economic power. Longitudinal data from men and women who were top 1% in mathematical reasoning ability at age 13, showed that even in women and men of similar abilities, men earned more than women later in life, and were more likely to be chief executives and employed in information technology and STEM positions (Lubinski, Benbow, & Kell, 2014). Finally, our analysis showed that there were also effects of raters' gender on some parental estimates. Male participants gave higher estimates than females to their parents on overall intelligence, interpersonal intelli- gence and intrapersonal intelligence. Females did not give significantly higher scores in any domain. Although the results of raters' gender effect were not always consistent through studies, those that reported differences in how genders estimated others usually showed that men were more prone to give higher IQ scores than women (Furnham et al., 2001; Swami et al., 2009). However, it is important to note that in our study differences were found in only three estimated domains and all of those effect sizes were relatively small (ηp2 = .02). Limitations and Conclusion The conducted study of twins’ self- and parental intelligence estimates yielded several relevant findings, but also has some limitations which can be taken into account when planning future research. Firstly, the twins’ mean correlation in their assessments of overall parental intelligence was substantial and we can rarely see rater-rater correlations, which are so high when judging the target traits. That correlation is higher than correlations of SAI and OAI with psychometrically tested intelligence. Thus, it may indicate the possibility that people use additional cues beyond intelligence in their subjective estimation of that trait. The future research migh be directed toward the identification of these cues. Behavioural genetic analysis of the assessed parental intelligence yielded substantial shared environmental effect indicating that these cues obviously lie in the same environment to which the twins are exposed. Bratko, Pocrnić, & Butković 241 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://www.psychopen.eu/ Secondly, it is obvious that twin agreement is substantially higher for overall intelligence than for the Gardner’s multiple intelligences. That is especially visible for the naturalistic and body kinaesthetic intelligence, which are probably difficult to judge for the raters. However, this may also indicate the lower validity of these Gardner’s theoretical concepts. Thus, future research on sources of the individual differences in SAI and OAI may benefit from other theoretical frameworks. For example, some of the studies in the field used Sternberg’s three types of intelligence (Furnham et al., 2009; Kang & Furnham, 2016; von Stumm et al., 2009), Thurstone's seven primary mental abilities (Ortner et al., 2011; Rammstedt & Rammsayer, 2000), 10 broad abilities from Cattell-Horn-Carroll theory of intelligence (Furnham & Mansi, 2014; Kang & Furnham, 2016) or concept of emotional intelligence (Petrides et al., 2004; von Stumm et al., 2009). Regarding gender effects, the expectations about males’ higher self-assessments for overall intelligence and for the masculine types of abilities were confirmed, while for the feminine types of abilities there were no signifi- cant gender effects. Both target and rater effects were found for the parental estimates of intelligence. One of the limitations of this research certainly lies in the fact that we only reported results on parental assessments of intelligence without parents’ scores on objective psychometric intelligence test. Thus, it is difficult to estimate to which extent obtained gender differences in other-assessments reflect the real individual differences in intelligence within the particular sample or the non-cognitive individual differences which might account for the observed parental differences. For SAI, the gender effect for the overall intelligence was controlled for the measured intelligence and personality. However, it should be noted that substantial (measured) gender differences are more probable for the specific abilities, and for those we do not have the control either for SAI or for the parental intelligence estimates. Future studies should therefore include both evaluations of the overall intelligence and specific abilities, as well as objectively measured general intelligence and specific abilities together with personality traits in order to test these different hypotheses. Notes i) All average correlations were calculated using the transformation from the original correlations to the Fisher's z-values, calculating the averages, and then using the back-transformation from the z-values to correlations Funding The authors have no funding to report. Competing Interests The authors have declared that no competing interests exist. Acknowledgments The authors have no support to report. References Ackerman, P. L., & Wolman, S. D. (2007). Determinants and validity of self-estimates of abilities and self-concept measures. Journal of Experimental Psychology, 13(2), 57-78. https://doi.org/10.1037/1076-898X.13.2.57 Twins' Assessing Their Own and Parental IQ 242 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.1037%2F1076-898X.13.2.57 https://www.psychopen.eu/ Bartley, S. J., Blanton, P. W., & Gilliard, J. L. (2005). Husbands and wives in dual-earner marriages: Decision-making, gender role attitudes, division of household labor, and equity. Marriage & Family Review, 37(4), 69-94. https://doi.org/10.1300/J002v37n04_05 Bartolac, A., & Kamenov, Ž. (2013). Percipirana raspodjela obiteljskih obveza među partnerima i doživljaj pravednosti u vezi. Sociologija i prostor, 51(1), 67-90. https://doi.org/10.5673/sip.51.1.4 Beloff, H. (1992). Mother, father and me: Our IQ. The Psychologist, 5, 309-311. Bennett, M. (1996). Men’s and women’s self-estimates of intelligence. The Journal of Social Psychology, 136(3), 411-412. https://doi.org/10.1080/00224545.1996.9714021 Bennett, M. (1997). Self-estimates of ability in men and women. The Journal of Social Psychology, 137(4), 540-541. https://doi.org/10.1080/00224549709595475 Bennett, M. (2000). Gender differences in the self-estimation of ability. Australian Journal of Psychology, 52, 23-28. https://doi.org/10.1080/00049530008255363 Borkenau, P., & Liebler, A. (1993). Convergence of stranger ratings of personality and intelligence with self-ratings, partner- rating and measured intelligence. Journal of Personality and Social Psychology, 65, 546-553. https://doi.org/10.1037/0022-3514.65.3.546 Bratko, D., Butkovic, A., Vukasovic, T., Chamorro-Premuzic, T., & von Stumm, S. (2012). Cognitive ability, self-assessed intelligence and personality: Common genetic but independent environmental aetiologies. Intelligence, 40, 91-99. https://doi.org/10.1016/j.intell.2012.02.001 Camarata, S., & Woodcock, R. (2006). Sex differences in processing speed: Developmental effects in males and females. Intelligence, 34(3), 231-252. https://doi.org/10.1016/j.intell.2005.12.001 Connelly, B. S., & Ones, D. S. (2010). An other perspective on personality: Meta-analytic integration of observers’ accuracy and predictive validity. Psychological Bulletin, 136(6), 1092-1122. https://doi.org/10.1037/a0021212 Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL, USA: Psychological Assessment Resources. Daseking, M., Petermann, F., & Waldmann, H. C. (2017). Sex differences in cognitive abilities: Analyses for the German WAIS-IV. Personality and Individual Differences, 114, 145-150. https://doi.org/10.1016/j.paid.2017.04.003 Davis, S. N. (2010). The answer doesn’t seem to change, so maybe we should change the question: A commentary on Lachance-Grzela and Bouchard. Sex Roles, 63(11-12), 786-790. https://doi.org/10.1007/s11199-010-9836-9 Flynn, J. R., & Rossi-Casé, L. (2011). Modern women match men on Raven’s Progressive Matrices. Personality and Individual Differences, 50(6), 799-803. https://doi.org/10.1016/j.paid.2010.12.035 Fox, G. L., & Murry, V. M. (2000). Gender and families: Feminist perspectives and family research. Journal of Marriage and Family, 62(4), 1160-1172. https://doi.org/10.1111/j.1741-3737.2000.01160.x Freund, P. A., & Kasten, N. (2012). How smart do you think you are? A meta-analysis on the validity of self-estimates of cognitive ability. Psychological Bulletin, 138(2), 296-321. https://doi.org/10.1037/a0026556 Bratko, Pocrnić, & Butković 243 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.1300%2FJ002v37n04_05 https://doi.org/10.5673%2Fsip.51.1.4 https://doi.org/10.1080%2F00224545.1996.9714021 https://doi.org/10.1080%2F00224549709595475 https://doi.org/10.1080%2F00049530008255363 https://doi.org/10.1037%2F0022-3514.65.3.546 https://doi.org/10.1016%2Fj.intell.2012.02.001 https://doi.org/10.1016%2Fj.intell.2005.12.001 https://doi.org/10.1037%2Fa0021212 https://doi.org/10.1016%2Fj.paid.2017.04.003 https://doi.org/10.1007%2Fs11199-010-9836-9 https://doi.org/10.1016%2Fj.paid.2010.12.035 https://doi.org/10.1111%2Fj.1741-3737.2000.01160.x https://doi.org/10.1037%2Fa0026556 https://www.psychopen.eu/ Funder, D. C. (1995). On the accuracy of personality judgment: A realistic approach. Psychological Review, 102, 652-670. https://doi.org/10.1037/0033-295X.102.4.652 Furnham, A. (2000). Parents’ estimates of their own and their children’s multiple intelligences. British Journal of Developmental Psychology, 18, 583-594. https://doi.org/10.1348/026151000165869 Furnham, A. (2001). Self-estimates of intelligence: Culture and gender differences in self and other estimates of general (g) and multiple intelligences. Personality and Individual Differences, 31, 1381-1405. https://doi.org/10.1016/S0191-8869(00)00232-4 Furnham, A., Arteche, A., Chamorro-Premuzic, T., Keser, A., & Swami, V. (2009). Self-and other-estimates of multiple abilities in Britain and Turkey: A cross-cultural comparison of subjective ratings of intelligence. International Journal of Psychology, 44(6), 434-442. https://doi.org/10.1080/00207590802644766 Furnham, A., & Chamorro-Premuzic, T. (2005). Estimating one’s own and one’s relatives’ multiple intelligence: A study from Argentina. The Spanish Journal of Psychology, 8(1), 12-20. https://doi.org/10.1017/S1138741600004911 Furnham, A., & Gasson, L. (1998). Sex differences in parental estimates of their children’s intelligence. Sex Roles, 38(1/2), 151-162. https://doi.org/10.1023/A:1018772830511 Furnham, A., Hosoe, T., & Tang, T. L. P. (2001). Male hubris and female humility? Crosscultural study of ratings of self, parental, and sibling multiple intelligence in America, Britain, and Japan. Intelligence, 30(1), 101-115. https://doi.org/10.1016/S0160-2896(01)00080-0 Furnham, A., Kosari, A., & Swami, V. (2012). Estimates of self, parental and partner multiple intelligences in Iran: A replication and extension. Iranian Journal of Psychiatry, 7(2), 66-73. Furnham, A., & Mansi, A. (2014). The self-assessment of the Cattell–Horn–Carroll broad stratum abilities. Learning and Individual Differences, 32, 233-237. https://doi.org/10.1016/j.lindif.2014.03.014 Furnham, A., & Mottabu, R. (2004). Sex and culture differences in the estimates of general and multiple intelligence: A study comparing British and Egyptian students. Individual Differences Research, 2(2), 82-96. Furnham, A., Rakow, T., Sarmany-Schuller, I., & De Fruyt, F. (1999). European differences in self-perceived multiple intelligences. European Psychologist, 4(3), 131-138. https://doi.org/10.1027//1016-9040.4.3.131 Furnham, A., & Rawles, R. (1995). Sex differences in the estimation of intelligence. Journal of Social Behavior and Personality, 10(3), 741-748. Furnham, A., & Shagabutdinova, K. (2012). Sex differences in estimating multiple intelligences in self and others: A replication in Russia. International Journal of Psychology, 47(6), 448-459. https://doi.org/10.1080/00207594.2012.658054 Furnham, A., & Storek, J. (2017). Hubris-humility effect and domain-masculine intelligence type in Czech Republic. Studia Psychologica, 59(3), 169-175. https://doi.org/10.21909/sp.2017.03.738 Furnham, A., & Wu, J. (2008). Gender differences in estimates of one’s own and parental intelligence in China. Individual Differences Research, 6(1), 1-12. Twins' Assessing Their Own and Parental IQ 244 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.1037%2F0033-295X.102.4.652 https://doi.org/10.1348%2F026151000165869 https://doi.org/10.1016%2FS0191-8869%2800%2900232-4 https://doi.org/10.1080%2F00207590802644766 https://doi.org/10.1017%2FS1138741600004911 https://doi.org/10.1023%2FA%3A1018772830511 https://doi.org/10.1016%2FS0160-2896%2801%2900080-0 https://doi.org/10.1016%2Fj.lindif.2014.03.014 https://doi.org/10.1027%2F%2F1016-9040.4.3.131 https://doi.org/10.1080%2F00207594.2012.658054 https://doi.org/10.21909%2Fsp.2017.03.738 https://www.psychopen.eu/ Furnham, A., Wytykowska, A., & Petrides, K. V. (2005). Estimates of multiple intelligences: A study in Poland. European Psychologist, 10(1), 51-59. https://doi.org/10.1027/1016-9040.10.1.51 Gardner, H. (1983). Frames of mind: A theory of multiple intelligences. New York, NY, USA: Basic Books. Gardner, H. (1999). Intelligence reframed. New York, NY, USA: Basic Books. Gardner, H. (2006). Multiple intelligences: New horizons. New York, NY, USA: Basic Books. Greven, C. U., Harlaar, N., Kovas, Y., Chamorro-Premuzic, T., & Plomin, R. (2009). More than just IQ: School achievement is predicted by self-perceived abilities - but for genetic rather than environmental reasons. Psychological Science, 20, 753-762. https://doi.org/10.1111/j.1467-9280.2009.02366.x Halpern, D. (2012). Sex differences in cognitive abilities (4th ed.). New York, NY, USA: Psychology press. Hogan, H. W. (1978). IQ self-estimates of males and females. The Journal of Social Psychology, 106, 137-138. https://doi.org/10.1080/00224545.1978.9924160 Howard, M. C., & Cogswell, J. E. (2018). The “other” relationships of self-assessed intelligence: A meta-analysis. Journal of Research in Personality, 77, 31-46. https://doi.org/10.1016/j.jrp.2018.09.006 Hyde, J. S., Fennema, E., & Lamon, S. J. (1990). Gender differences in mathematics performance: A meta-analysis. Psychological Bulletin, 107(2), 139-155. https://doi.org/10.1037/0033-2909.107.2.139 Irwing, P. (2012). Sex differences in g: An analysis of the US standardization sample of the WAIS-III. Personality and Individual Differences, 53(2), 126-131. https://doi.org/10.1016/j.paid.2011.05.001 Kang, W., & Furnham, A. (2016). Gender and personality differences in the self-estimated intelligence of Koreans. Psychology, 7(8), 1043-1052. https://doi.org/10.4236/psych.2016.78105 Keith, T. Z., Reynolds, M. R., Patel, P. G., & Ridley, K. P. (2008). Sex differences in latent cognitive abilities ages 6 to 59: Evidence from the Woodcock–Johnson III tests of cognitive abilities. Intelligence, 36(6), 502-525. https://doi.org/10.1016/j.intell.2007.11.001 Kruger, J. (1999). Lake Wobegon be gone! The" below-average effect" and the egocentric nature of comparative ability judgments. Journal of Personality and Social Psychology, 77(2), 221-232. https://doi.org/10.1037/0022-3514.77.2.221 Lachance-Grzela, M., & Bouchard, G. (2010). Why do women do the lion’s share of housework? A decade of research. Sex Roles, 63(11-12), 767-780. https://doi.org/10.1007/s11199-010-9797-z Lubinski, D., Benbow, C. P., & Kell, H. J. (2014). Life paths and accomplishments of mathematically precocious males and females four decades later. Psychological Science, 25(12), 2217-2232. https://doi.org/10.1177/0956797614551371 McGue, M., Bacon, S., & Lykken, D. T. (1993). Personality stability and change in early adulthood: A behavioral genetic analysis. Developmental Psychology, 29(1), 96-109. https://doi.org/10.1037/0012-1649.29.1.96 Neale, M. C., Boker, S. M., Xie, G., & Maes, H. H. (2006). Mx: Statistical modeling (7th ed.). Richmond, VA, USA: Department of Psychiatry. Neale, M. C., & Maes, H. H. M. (2004). Methodology for genetic studies of twins and families. Dordrecht, The Netherlands: Kluwer Academic Publishers. Bratko, Pocrnić, & Butković 245 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.1027%2F1016-9040.10.1.51 https://doi.org/10.1111%2Fj.1467-9280.2009.02366.x https://doi.org/10.1080%2F00224545.1978.9924160 https://doi.org/10.1016%2Fj.jrp.2018.09.006 https://doi.org/10.1037%2F0033-2909.107.2.139 https://doi.org/10.1016%2Fj.paid.2011.05.001 https://doi.org/10.4236%2Fpsych.2016.78105 https://doi.org/10.1016%2Fj.intell.2007.11.001 https://doi.org/10.1037%2F0022-3514.77.2.221 https://doi.org/10.1007%2Fs11199-010-9797-z https://doi.org/10.1177%2F0956797614551371 https://doi.org/10.1037%2F0012-1649.29.1.96 https://www.psychopen.eu/ Neto, F., & Furnham, A. (2011). Sex differences in parents’ estimations of their own and their children’s multiple intelligences: A Portuguese replication. The Spanish Journal of Psychology, 14(1), 99-110. https://doi.org/10.5209/rev_SJOP.2011.v14.n1.8 Neto, F., Furnham, A., & da Conceição Pinto, M. (2009). Estimating one’s own and one’s relatives’ multiple intelligence: A cross-cultural study from East Timor and Portugal. The Spanish Journal of Psychology, 12(2), 518-527. https://doi.org/10.1017/S113874160000189X Ortiz, S. O. (2015). CHC theory of intelligence. In S. Goldstein, D. Princiotta, & J. A. Naglieri (Eds.), Handbook of intelligence (pp. 209-227). New York, NY, USA: Springer. Ortner, T. M., Müller, S. M., & Garcia-Retamero, R. (2011). Estimations of parental and self intelligence as a function of parents’ status: A cross-cultural study in Germany and Spain. Social Science Research, 40(4), 1067-1077. https://doi.org/10.1016/j.ssresearch.2011.03.006 Petrides, K. V., Furnham, A., & Martin, G. N. (2004). Estimates of emotional and psychometric intelligence: Evidence for gender-based stereotypes. The Journal of Social Psychology, 144(2), 149-162. https://doi.org/10.3200/SOCP.144.2.149-162 Polderman, T. J., Benyamin, B., De Leeuw, C. A., Sullivan, P. F., Van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47(7), 702-709. https://doi.org/10.1038/ng.3285 Rammstedt, B., & Rammsayer, T. H. (2000). Sex differences in self-estimates of different aspects of intelligence. Personality and Individual Differences, 29(5), 869-880. https://doi.org/10.1016/S0191-8869(99)00238-X Reed, T., Plassman, B. L., Tanner, C. M., Dick, D. M., Rinehart, S. A., & Nichols, W. C. (2005). Verification of self-report of zygosity determined via DNA testing in a subset of the NAS-NRC twin registry 40 years later. Twin Research and Human Genetics, 8(4), 362-367. https://doi.org/10.1375/twin.8.4.362 Reynolds, M. R., Keith, T. Z., Ridley, K. P., & Patel, P. G. (2008). Sex differences in latent general and broad cognitive abilities for children and youth: Evidence from higher-order MG-MACS and MIMIC models. Intelligence, 36(3), 236-260. https://doi.org/10.1016/j.intell.2007.06.003 Savage-McGlynn, E. (2012). Sex differences in intelligence in younger and older participants of the Raven’s Standard Progressive Matrices Plus. Personality and Individual Differences, 53(2), 137-141. https://doi.org/10.1016/j.paid.2011.06.013 Song, Y. M., Lee, D. H., Lee, M. K., Lee, K., Lee, H. J., Hong, E. J., . . . Sung, J. (2010). Validity of the zygosity questionnaire and characteristics of zygosity-misdiagnosed twin pairs in the Healthy Twin Study of Korea. Twin Research and Human Genetics, 13(3), 223-230. https://doi.org/10.1375/twin.13.3.223 Spinath, F. M., Spinath, B., & Plomin, R. (2008). The nature and nurtureof intelligence and motivation in the origins of sex differences inelementary school achievement. European Journal of Personality, 22, 211-229. https://doi.org/10.1002/per.677 Sternberg, R. J. (2014). Teaching about the nature of intelligence. Intelligence, 42, 176-179. https://doi.org/10.1016/j.intell.2013.08.010 Twins' Assessing Their Own and Parental IQ 246 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.5209%2Frev_SJOP.2011.v14.n1.8 https://doi.org/10.1017%2FS113874160000189X https://doi.org/10.1016%2Fj.ssresearch.2011.03.006 https://doi.org/10.3200%2FSOCP.144.2.149-162 https://doi.org/10.1038%2Fng.3285 https://doi.org/10.1016%2FS0191-8869%2899%2900238-X https://doi.org/10.1375%2Ftwin.8.4.362 https://doi.org/10.1016%2Fj.intell.2007.06.003 https://doi.org/10.1016%2Fj.paid.2011.06.013 https://doi.org/10.1375%2Ftwin.13.3.223 https://doi.org/10.1002%2Fper.677 https://doi.org/10.1016%2Fj.intell.2013.08.010 https://www.psychopen.eu/ Storek, J. (2011). The hubris and humility effect and the domain-masculine intelligence type: Exploration of determinants of gender differences in selfestimation of ability (Unpublished doctoral dissertation). London, United Kingdom: University College London. Swami, V., Furnham, A., & Zilkha, S. (2009). Estimates of self, parental, and partner multiple intelligence and their relationship with personality, values, and demographic variables: A study in Britain and France. The Spanish Journal of Psychology, 12(2), 528-539. https://doi.org/10.1017/S1138741600001906 Syzmanowicz, A., & Furnham, A. (2011). Gender differences in self-estimates of general, mathematical, spatial and verbal intelligence: Four meta analyses. Learning and Individual Differences, 21(5), 493-504. https://doi.org/10.1016/j.lindif.2011.07.001 Tarbuk, D. (1977). Test 4/MFBT – Rjecnik [Vocabulary]. Prirucnik za psihologijsko ispitivanje s pomoću baterije MFBT: forma P-1 [Manual]. Zagreb, Croatia. Torgersen, S. (1979). The determination of twin zygosity by means of a mailed questionnaire. Acta Geneticae Medicae et Gemellologiae, 28(3), 225-236. https://doi.org/10.1017/S0001566000009077 van der Linden, D., Dunkel, C. S., & Madison, G. (2017). Sex differences in brain size and general intelligence (g). Intelligence, 63, 78-88. https://doi.org/10.1016/j.intell.2017.04.007 von Stumm, S., Chamorro-Premuzic, T., & Furnham, A. (2009). Decomposing self-estimates of intelligence: Structure and gender differences across 12 nations. British Journal of Psychology, 100, 429-442. https://doi.org/10.1348/000712608X357876 Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin, 117(2), 250-270. https://doi.org/10.1037/0033-2909.117.2.250 World Economic Forum. (2018, March 9). Global Gender Gap Report 2018 [World Economic Forum]. Retrieved from https://www.weforum.org/reports/the-global-gender-gap-report-2018 Yuen, M., & Furnham, A. (2006). Sex differences in self-estimation of multiple intelligences among Hong Kong Chinese adolescents. High Ability Studies, 16(2), 187-199. https://doi.org/10.1080/13598130600618009 Zipp, J. F., Prohaska, A., & Bemiller, M. (2004). Wives, husbands, and hidden power in marriage. Journal of Family Issues, 25(7), 923-948. https://doi.org/10.1177/0192513X04267151 About the Authors Denis Bratko is a distinguished professor at the Department of Psychology at the Faculty of Humanities and Social Sciences, University of Zagreb, where he leads the Chair for General Psychology. His research interests are individual differences, primarily in personality and ability domains. Besides that, he is interested in behavioural genetics, cross-cultural psychology, and interrelations between dispositions and socially relevant life outcomes. He published his work in many distinguished scientific journals and regularly serves as a reviewer and/or member of the editorial board in some of the leading journals in his field. Bratko, Pocrnić, & Butković 247 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 https://doi.org/10.1017%2FS1138741600001906 https://doi.org/10.1016%2Fj.lindif.2011.07.001 https://doi.org/10.1017%2FS0001566000009077 https://doi.org/10.1016%2Fj.intell.2017.04.007 https://doi.org/10.1348%2F000712608X357876 https://doi.org/10.1037%2F0033-2909.117.2.250 https://www.weforum.org/reports/the-global-gender-gap-report-2018 https://doi.org/10.1080%2F13598130600618009 https://doi.org/10.1177%2F0192513X04267151 https://www.psychopen.eu/ Martina Pocrnić is a research assistant at the Chair for General Psychology at the Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb. She is interested in personality psychology, behavioural genetics, and relations between dispositions and socially relevant behaviours. Ana Butković is an assistant professor at the Chair for General Psychology at the Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb. Her research interests are personality, intelligence, behavioural genetics and psychology of music. She published articles in many highly ranked journals and often serves as a reviewer for them. Twins' Assessing Their Own and Parental IQ 248 Europe's Journal of Psychology 2020, Vol. 16(2), 229–248 https://doi.org/10.5964/ejop.v16i2.1853 PsychOpen GOLD is a publishing service by Leibniz Institute for Psychology Information (ZPID), Trier, Germany. www.leibniz-psychology.org https://www.leibniz-psychology.org/ https://www.psychopen.eu/ Twins' Assessing Their Own and Parental IQ (Introduction) Association Between Subjectively Assessed and Measured Intelligence The Twin Studies of Subjectively Assessed Intelligence The Hubris-Humility Effect Gender Effect in Intelligence Assessment of Others Sources of Gender Differences Rater Effect The Present Study Method Participants Measures and Procedure Results Rater Agreement and Behavioural Genetic Analysis of Parental Estimates of Intelligence Gender Differences in Self-Assessed Intelligence Effect of Raters’ and Targets’ Gender in Parental Estimates of Intelligence Discussion Twin Agreement and Behavioural Genetic Analysis of Parental Estimates of Intelligence Gender Differences in Self-Assessed Intelligence Effect of Raters’ and Targets’ Gender in Parental Estimates of Intelligence Limitations and Conclusion Notes (Additional Information) Funding Competing Interests Acknowledgments References About the Authors