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Genetic and environmental influences on the EPQ-RS scales: a twin study using self- and peer reports
Personality and Individual Differences 37 (2004) 579–590 www.elsevier.com/locate/paid
Genetic and environmental influences on the EPQ-RS scales: a twin study using self- and peer reports Heike Wolf a
a,*
, Alois Angleitner b, Frank M. Spinath b, Rainer Riemann a, Jan Strelau c
Friedrich-Schiller-Universit€at Jena, Department of Psychology, Humboldtstr. 26 D-00743, Jena, Germany b University of Bielefeld, Department of Psychology, P.O. Box 10 01 31, 33501 Bielefeld, Germany c University of Warsaw, Faculty of Psychology, ul. Stawki 517, PL-00183 Warsaw, Poland Received 6 March 2003; received in revised form 11 September 2003; accepted 29 September 2003 Available online 19 November 2003
Abstract We examined genetic and environmental influences on the scales of the German Eysenck Personality Questionnaire-RS (EPQ-RS) in a sample of 496 monozygotic, 181 same-sex, and 68 opposite-sex dizygotic adult twin pairs. Along with other questionnaires each participant completed the EPQ-RS and was also described by two independent peers on a peer report form of the EPQ-RS. Based on this design it was possible to analyse not only the standard univariate twin model but more powerful multivariate models to estimate the genetic and environmental sources of variance on phenotypic individual differences. Partly because latent variables are error free, the joint analyses of self- and peer report data yielded genetic contributions to phenotypic variance that were substantially higher than typically found in univariate analyses based on self-report data alone (h2 ¼ 0:67–0:86). These high genetic correlations between self- and peer reports provide evidence for the validity of personality ratings. Ó 2003 Elsevier Ltd. All rights reserved. Keywords: EPQ-RS; Personality; Twins; Genetics; Self- and peer reports
1. Introduction Behavior genetic research in the field of personality provides consistent evidence for a substantial genetic influence on major dimensions of personality (Bouchard, 1997; Eaves, Eysenck,
*
Corresponding author. Tel.: +49-36-41-94-51-63; fax: +49-36-41-94-51-62. E-mail address: [email protected] (H. Wolf).
0191-8869/$ - see front matter Ó 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2003.09.028
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& Martin, 1989). One of the most influential models in the field of personality focuses on three major personality factors, namely Psychoticism (P), Extraversion (E), and Neuroticism (N) (Eysenck & Eysenck, 1985). Numerous studies using the Eysenck Personality Questionnaire (EPQ; Eysenck & Eysenck, 1975) or related inventories measuring the PEN model found substantial genetic effects on all three of EysenckÕs personality factors, (e.g., Eaves et al., 1989; Martin & Jardine, 1986). A meta-analysis of early twin studies yielded heritability estimates (h2 ) for P, E, and N of 0.46, 0.58, and 0.44, respectively (Eaves et al., 1989). The authors report evidence from two large twin studies and one study of extended kinship. Heritability estimates fall between 0.40 and 0.53 for the three personality factors. Although these findings demonstrate substantial genetic influence on interindividual differences in personality, the magnitude of the estimates also indicate that environmental factors are equally important. However, this environmental influence is almost entirely of the nonshared environmental variety. Loehlin and Martin (2001) reported age trends in heritabilities of the Eysenck personality dimensions. Results of model-fitting for same-sex twin pairs in three age groups were in agreement with results from previous studies. For Extraversion and Neuroticism heritability estimates were 0.47 and 0.40, respectively. Merely for Psychoticism the heritability estimate of 0.28 was lower. Significant age differences in the genetic or environmental parameters could not be found for any of the three personality traits P, E, and N (Loehlin & Martin, 2001). In general, the data summarized here indicates substantial heritability for all the dimensions of the EPQ. Genetic factors explain about 50% of the variance in personality traits (Eysenck, 1990). On the other hand, environmental influences shared by siblings or twins contribute only marginally to personality differences (Bouchard, 1994; Eysenck, 1990). It is noteworthy that these conclusions for adult personality measures rely almost exclusively on self-reports. Because self-reports are known to be prone to particular biases, the inclusion of peer reports into behavior-genetic studies of personality provides a valuable extension of the traditional approach (Riemann, Angleitner, & Strelau, 1997). The assessment of peer report data allows a validation of the results from self-report studies. Furthermore, the inclusion of another source of data permits separating the influence of nonshared environmental effects from measurement error. As pointed out in previous studies (e.g. Borkenau, Riemann, Spinath, & Angleitner, 2000; Hofstee, 1994; Riemann et al., 1997) one shortcoming of self-report data is that such personality judgments do not directly reflect behavioral differences. Responses to questionnaire items or rating scales require inferences and interpretations. Thus, heritability coefficients or estimates of environmental influences might not only reflect content variance but also variance in individual response styles. Second, Borkenau et al. (2000) also argued that self-reports may be distorted by ‘‘contrast effects’’. These effects result in an underestimation of the similarity between DZ twins and may obscure shared environmental effects (Spinath & Angleitner, 1998). Contrast effects might arise from an exaggeration of real behavioral differences between twin siblings if twins compare their own behavior to the behavior of their co-twin rather than to the population average. It is also possible that MZ twins discount behavioral differences because of their generally high similarity. The use of peer reports in addition to self-reports is one way to overcome contrast effects, especially if peers judge only one twin of a pair. Ideally, information is gathered from peers who know only one of the twins very well and have little or no contact with the other twin sibling.
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The validity of peer reports in personality research has been widely demonstrated (Funder, 1987; Kenny, 1991, 1994). Peer reports consistently show substantial positive correlations both among each other and with self-report data (Funder & Colvin, 1997). In the study mentioned above (Riemann et al., 1997) self- and peer reports of the NEO FiveFactor Inventory (NEO-FFI; Costa & McCrae, 1989) were collected. The NEO-FFI is a standard inventory for the assessment of the dimensions of the Five-Factor model (Goldberg, 1993; John & Srivastava, 1999; McCrae & Costa, 1997) measuring the five broad personality factors Neuroticism, Extraversion, Openness to Experience, Conscientiousness, and Agreeableness. Analyses of the self-report data replicated earlier findings of a substantial genetic influence on the personality dimensions of the Five-Factor model with heritability estimates between 0.42 and 0.53 on all broad NEO-FFI dimensions. A similar pattern of results was found for peer reports yielding even higher heritability estimates, because measurement error was controlled for. Thus, Riemann et al. (1997) concluded that self-report studies of single personality measures tend to underestimate genetic influences because they do not allow the separation of error variance from variance due to specific environmental influences. Reconsidering the results of behavioral genetic self-report studies on the three factors of the Eysenckian personality model clearly displays great similarities to influences of genetic and environmental factors on the dimensions of the five-factor model. While Riemann et al. (1997) analyzed genetic and environmental influences on peer reports of the Five-Factor model, to our knowledge no study has reported similar analyses for the Eysenckian personality factors. Therefore, the present study is a continuation of the analyses of the genetic and environmental influences on the EPQ-RS scales based on self- and peer reports presented by Angleitner, Riemann, and Strelau (1997). The main purpose of this continuation is to estimate genetic and environmental influences on the dimensions of the EPQ-RS using self- and peer report data in joint analyses similar to the analyses presented by Riemann et al. (1997) on self- and peer report ratings of the NEO-FFI. The multivariate design provides the opportunity to estimate effects due to nonshared environmental influences on personality traits separately from measurement error. Thus, heritability estimates derived from multimethod sources of assessment are important to corroborate results from single modes of assessment. Furthermore, through the joint analyses of self- and peer report data it is possible to estimate genetic and environmental influences on broad personality traits (constructs) measured by independent judges. Finally, genetic and environmental correlations will be estimated between self- and peer report measures. The structure of these correlations provides information about genetic and environmental mediation of the covariance between self- and peer reports. Separate analyses of both data sources are valuable in that they can validate one another. However, a similar quantitative etiological estimate might still reflect qualitatively different influences. Joint analyses of self- and peer reports are required to address etiological sources of the covariation between traits or different modes of assessment directly.
2. Method The study presented is part of the Bielefeld–Warsaw Twin Project chaired by Alois Angleitner and Jan Strelau. From the total German sample we selected those participants who completed the
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questionnaires relevant for the present study. Thus, participants were 496 MZ twin pairs, 181 same-sex DZ twin pairs (DZss) and 68 opposite-sex DZ twin pairs (DZos). Their age varied between 17 and 83 years with a mean of 33.9 years (SD ¼ 13.0 years). Considering same-sex twin pairs, women (542 pairs) participated more frequently than men (135 pairs). Gender was not significantly associated with zygosity. All twin pairs were volunteers recruited through newspaper and media announcements. Zygosity was determined using a physical similarity questionnaire (Oniszczenko, Angleitner, Strelau, & Angert, 1993) in which participants were asked to describe and compare themselves with their co-twins on a number of physical characteristics. This questionnaire was validated in a subsample of 122 (84 MZ, 38 DZ) same-sex twin pairs by means of DNA analysis yielding a highly satisfying correct classification rate (93.6%). This is in good agreement with other studies assessing the validity of zygosity questionnaires (Lykken, 1978; Plomin, DeFries, & McClearn, 1990). Misclassifications were more likely to the effect that DZ twins were classified as monozygotic (6 cases) than classifying MZ twins as dizygotic (one case).
3. Measures All twin pairs completed a set of temperament and personality questionnaires at home (see Spinath et al., 1999; for a detailed overview of these sets). Among these measures were the selfand peer report versions of the German short form of the Revised Eysenck Personality Questionnaire (EPQ-RS: Eysenck & Eysenck, 1991; Ruch, 1999). The peer report version of the EPQRS was identical to the self-report version, except that the items were reformulated in the third person form. Participants were instructed to complete the questionnaires independently of one another in a nondistracting setting. In addition, each twin was asked to give the peer report versions of the questionnaires to two peers who preferably knew the respective twin but not the co-twin well. Subjects returned self- and peer reports by mail; to guarantee anonymity the latter were sealed by the peers in separate envelopes. The EPQ-RS was developed by Eysenck and Eysenck (1991) for the economic measurement of the dimensions Psychoticism (P), Extraversion (E), and Neuroticism (N). A control scale (Lie, L) is also included in the questionnaire. The original English version contains 48 items––12 items per scale. The German EPQ-RS (Ruch, 1999) comprises 50 items––14 items to measure P and 12 items for each of the three remaining scales. Psychometric properties of the German translation are good and similar to those of the original EPQ-RS (Ruch, 1999).
4. Analyses Prior to behavior genetic analyses, all scores were regressed on age and sex. This has become a standard procedure in twin research, particularly in samples covering a large age range because monozygotic and same-sex dizygotic pairs are perfectly correlated for gender and age, so any similarity between these twins will be spuriously increased if gender and age effects are present for the variable in question (McGue & Bouchard, 1984).
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Behavior genetic analyses were carried out only for the content scales of the EPQ-RS, that is Psychoticism, Extraversion, and Neuroticism, because the Lie scale was originally designed as a validity scale assessing the presence of response sets such as social naivete or conformity in the EPQ-R. In the present study, we did not analyse this scale because the status of the Lie scale as a personality trait remains unclear. Intraclass correlations (ICC 1.1; Shrout & Fleiss, 1979) were calculated as a measure of twin similarity for the three content scales separately for the self- and the peer report data. We used multivariate maximum-likelihood model fitting to estimate the influence of genetic and environmental sources of variance on phenotypic individual differences because multivariate designs have greater power to detect smaller genetic and environmental influences than univariate designs (Schmitz, Cherny, & Fulker, 1998). Note that for these analyses opposite-sex twin pairs were omitted because they are not as comparable to MZ twin pairs. Given that the present study assessed self- and peer reports, a multivariate model including three different raters (one self- and two peer reports) per target person can be fitted to the data. The joint analysis of self- and peer report data also yields estimates separately interpretable for self- and peer reports which are comparable to separate univariate analyses. Self- and averaged peer report data was analysed simultaneously using the computer program Mx (Neale, Boker, Xie, & Maes, 1999) to estimate genetic and environmental influences on the latent phenotype independently of possible rater bias and unreliability of the ratings. The analyses were based on variance-covariance matrices. Our models specified additive genetic effects (A), genetic dominance effects (D), shared environmental effects (C), and nonshared environmental effects (E). In analyses based exclusively on self-report data (not reported in the present study), E is a confound of variance due to nonshared environmental effects and measurement error. In multivariate analyses error variance can be separated from nonshared environmental variance. Genetic dominance and shared environmental effects were fitted alternatively. The models were systematically modified to drop A, D or C and E effects to test their significance. The fit criteria used to determine the ‘‘best-fitting’’ model were chi-square differences, the principle of parsimony and root mean square error of approximation. Overall goodness-of-fit was assessed with v2 and AkaikeÕs Information criterion (Akaike, 1987: AIC ¼ v2 2df). The AIC was used to decide between (unnested) models that both fitted the data according to the chi-square criterion. The models fitted to our data are depicted in Fig. 1. Model 1––the latent factor model with method effects––is based on the rater bias model described by Neale and Cardon (1992). Although self- and peer reports were provided by different judges for each twin, method factors were included in the model because the similarity among selfand among peer ratings, even if they stem from different persons, may be greater than the similarity between self- and peer ratings. Model 2 is more parsimonious than model 1 since it does not include method factors. Due to the availability of self- and peer reports it is possible to perform bivariate analyses to estimate genetic (rG ), shared (rC ), and nonshared (rE ) environmental correlations which estimate the extent to which two variables share genetic, shared or nonshared environmental variance (Fig. 2). Although in standard bivariate behavioral genetic analyses, rG , rC , and rE are estimated to explain the covariation between different traits, it is also informative to estimate the extent to which genetic or environmental factors contribute to the observed correlation between methods,
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H. Wolf et al. / Personality and Individual Differences 37 (2004) 579–590 MZ r=1.0/DZ r=.25 r=1.0
C
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MZ r=1.0/ DZ r=.5
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P Tw1
P Tw2
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R s1
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R p1 9
8 R s2
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R p2 10
Bs
(a)
Av. Peer Tw2
Self Tw2
8
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Av. Peer Tw1
Self Tw1
D 3
Bp
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MZ r=1.0/ DZ r=.5
C
A
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Self Tw1
P Tw2 6
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Av. Peer Tw1
8
7
(b)
R s1
E
3 4
P Tw1 5
D
R p1
Self Tw2
7
Av. Peer Tw2
8 R s2
R p2
Fig. 1. Latent factor models with and without method effects for the joint analysis of self- and peer report data. (a) Latent factor model with method effects (rater bias model) for the joint analysis of self- and peer report data and (b) latent factor model without method effects for the joint analysis of self- and peer report data. Note: (a) The variance of the phenotypic trait was constrained to unity. Paths 5 and 6 and paths 7 and 8 were constrained to be equal for twins and co-twins as well as for MZ and DZ twins. Paths 9 and 10 were estimated for each method (self- vs. peer report) separately. They were constrained to be equal within methods and between MZ and DZ twin groups. A ¼ additive genetic effects; C ¼ shared environmental influences; D ¼ genetic dominance effects; E ¼ specific environmental influences; P Tw1 and P Tw2 ¼ phenotype of twin 1 or 2; self Tw1 and Self Tw2 ¼ self-report of twin 1 or 2; av. peer Tw1 and av. peer Tw2 ¼ peer report (averaged across two raters) on twin 1 or 2; BS ¼ method effects for self-reports; BP ¼ method effects for peer reports; RS and RP ¼ measures error variance.
for example, self- and peer reports. Bivariate rG , rC , and rE are estimated by fitting a structural equation model known as ‘‘Cholesky decomposition’’ (see Neale & Cardon, 1992) using the computer program Mx (Neale et al., 1999). In addition to rG , rC , and rE it is also informative to compute the proportion of the phenotypic correlation between self- and peer reports that is mediated by either genetic or environmental influences. This proportion can not be derived directly from the genetic and environmental correlation alone as it depends in part on the estimates of genetic and environmental influences from the univariate or in this case multivariate analyses of self- and averaged peer report data (Loehlin, 1996).
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rE rC rG E
C
eS
cS
A
A
C
eP
aS
Selfreport
cP
E
aP
av. Peer report
Fig. 2. Simplified correlated factors model for the analysis of the etiology of the relation between self- and peer reported personality. Note: See text for description of the model. A ¼ additive genetic effects; C ¼ shared environmental influences; E ¼ specific environmental influences; as , cs and es ¼ additive genetic, shared and nonshared environmental influences on self-reported personality; ap , cp and ep ¼ additive genetic, shared and nonshared environmental influences on peer reported personality; rG ¼ genetic correlation; rC ¼ shared environmental correlation; rE ¼ nonshared environmental correlation.
5. Results Internal consistencies (coefficient alphas) of the EPQ-RS self- and peer report scales ranged from 0.59 to 0.84 (mean 0.74) for self-reports and from 0.67 to 0.86 (mean 0.77) for peer reports. For all scales, internal consistencies were marginally higher for the peer report data. For both ratings (self- and peer reports), internal consistencies were lowest for Psychoticism. The two peer raters showed a satisfactory agreement of 0.57 on average. Correlations between self-reports and averaged peer reports were in the range of 0.47 to 0.82 (mean 0.68), indicating high validity for the self- and peer report measures. Twin similarities (ICC 1.1) for the EPQ-RS scales are given in Table 1 for the self- as well as for the peer report data. Table 1 Intraclass correlations (ICC 1,1) of the EPQ-RS self- and averaged peer report scales for MZ and DZ twins MZ (N ¼ 496)
DZss (N ¼ 181)
DZos (N ¼ 68)
Self-reports Psychoticism Extraversion Neuroticism
0.44 0.57 0.56
0.23 0.20 0.11
0.19 0.18 )0.07
Mean
0.53
0.18
0.10
Peer reports Psychoticism Extraversion Neuroticism
0.43 0.47 0.36
0.27 0.19 0.26
0.19 0.19 0.07
Mean
0.42
0.24
0.15
Note: Statistics are based on scores corrected for age and gender effects.
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Similarity correlations for MZ twins exceeded those of DZ twins for all scales regardless of the method used (self- or peer reports). For self-reported Extraversion and Neuroticism, the magnitude of the MZ twins correlations was greater than twice the similarity of the DZ twins. This pattern was replicated through peer reports for one of the two scales, namely Extraversion, indicating that a proportion of the overall or broad genetic influence might be due to nonadditive genetic effects. Goodness-of-fit statistics and parameter estimates from the multivariate analyses for the EPQRS scales with and without method factors are displayed in Table 2. As described above, we first tested a latent factor model with method effects (rater bias model). Overall, the reduced AE model yielded an appropriate fit to the data for all three scales. The inclusion of shared environmental variance improved the fit for Psychoticism only marginally (v2 difference ¼ 0.76, df ¼ 1, ns). For Extraversion, the ACE model was rejected at the 0.05 level. Allowing for genetic dominance did not improve the fit significantly compared to the more parsimonious AE model (v2 difference ¼ 1.67, df ¼ 1, ns). For all scales and regardless of the inclusion or exclusion of method factors, a model without genetic factors (CE and E) was rejected. For Neuroticism, genetic dominance was an important source of variance. The inclusion of D improved the fit significantly (v2 difference ¼ 4.61, df ¼ 1, p < 0:05). However, fitting an ADE model for the Neuroticism data resulted in a parameter estimate of zero for additive genetic variance. Hence, a reduced DE model yielded the same fit. Because the existence of genetic dominance effects without influences of additive genetic variance is considered to be unlikely (Roberts, 1967), we decided to favor the AE model as a parsimonious and theoretically coherent alternative. For Extraversion and Neuroticism the model with method factors fitted the data significantly better than the model without method factors although the estimated method effects for Extraversion were small. For Psychoticism there was no significant difference in model fit between the model with and the model without method factors. Repeating the analyses with raw data yielded virtually identical results. Table 2 Model-fitting results for the joint analyses of self- and peer report data with and without method factors Model fit v2
Fit indices RMSEA
a2
d2
e2
b2s
b2p
Latent factor model with method effects P AE 12.00 13 0.53 E AE 15.20 13 0.30 N ADE 13.81 12 0.31 AE 18.42 13 0.14
0.000 0.023 0.018 0.028
0.82 0.67 0.66 0.00
– – 0.68 –
0.18 0.34 0.32 0.33
0.03 0.00 0.00 0.00
0.04 0.06 0.15 0.15
Latent factor model without P AE 14.63 E AE 24.16 N ADE 39.57 AE 43.38
0.010 0.025 0.063 0.070
0.86 0.68 0.00 0.74
– – 0.74 –
0.14 0.32 0.26 0.26
– – – –
– – – –
df
p
method effects 15 0.48 15 0.06 14 0.00 15 0.00
Note: The analyses are based on age- and sex-corrected data from 496 MZ and 181 same-sex DZ twin pairs. See text for description of the models. P ¼ psychoticism; E ¼ extraversion; N ¼ neuroticism; A ¼ additive genetic effects; E ¼ specific environmental effects and error influences; D ¼ genetic dominance effects. b2s ¼ parameter estimates for the methodeffects due to self-reports; b2p ¼ parameter estimates for the method-effects due to peer reports. df ¼ degrees of freedom.
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Table 3 Results from bivariate model-fitting analyses for self- and peer reported EPQ-RS scales P E N
v2
p (df ¼ 14)
rG
rE
rG c
rE c
11.65 12.35 20.71
0.63 0.58 0.11
0.90 [0.80; 1.00] 0.91 [0.85; 0.96] 0.76 [0.67; 0.85]
0.15 [0.07; 0.23] 0.48 [0.42; 0.55] 0.31 [0.23; 0.38]
0.82 0.66 0.67
0.18 0.34 0.33
Note: The analyses are based on age- and sex-corrected data from 496 MZ and 181 same-sex DZ twin pairs. P ¼ psychoticism; E ¼ extraversion; N ¼ neuroticism; rG ¼ genetic correlation, rE ¼ nonshared environmental correlation, rG c ¼ proportion of the phenotypic correlation due to genetic mediation, rE c ¼ proportion of the phenotypic correlation due to nonshared environmental mediation. Confidence intervals (95%) for rG and rE are provided in brackets.
Table 3 shows the results from bivariate model fitting analyses of self- and peer reports on the EPQ-RS scales. An AE model fitted the data best. Genetic correlations ranged from 0.76 for Neuroticism to 0.91 for Extraversion. Environmental correlations were substantially smaller. The two rightmost columns of Table 3 present the proportions of the phenotypic correlations that are mediated by genetic or environmental influences. As can be seen, for all scales the major proportion of the phenotypic correlation was due to genetic mediation ranging from 67% for Neuroticism to 82% for Psychoticism. 6. Discussion The present study investigated the etiology of the Eysenckian personality traits in a multimethodological way. Apart from self-reports of personality each twin was described by two peers on peer-report versions of the same questionnaires. Thus, on the one hand, the present study could be viewed as a replication study. The analyses of the self-report data support earlier findings (e.g., Eaves et al., 1989; Martin & Jardine, 1986) of substantial genetic influences on all broad personality dimensions. Consistent differences between the three broad scales are hardly noticeable across studies. The present study found MZ correlations between 0.44 and 0.57 and same-sex DZ correlations between 0.11 and 0.23, which are comparable to results reported by Bouchard (1997). In the group of opposite-sex DZ twins we found an insignificant negative correlation (rDZos ¼ 0:07) for Neuroticism which could be due to contrast effects (Spinath & Angleitner, 1998) but could also be due to differences in the etiology of Neuroticism between males and females. Analyses of the peer report data in the present study clearly demonstrated family resemblance for the three personality dimensions with MZ twin correlations between 0.36 and 0.47 and samesex DZ twin correlations between 0.19 and 0.27. Thus, a comparison of the results for self-report and peer report data across the EPQ-RS scales displayed substantial similarity. Estimating genetic and environmental influences on the basis of peer report measures represents an advantage compared to estimates on the basis of self-report measures alone because the analyses of a latent variable with loadings from the two peer reports per twin allows the separation of error variance from nonshared environmental influences. Estimates of genetic influences derived from peer report data were found to be somewhat higher than from self-reports. For example, Riemann et al.
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(1997) who measured the Big Five traits by the German version of the NEO-FFI found an increase in the averaged estimates of genetic influences from 0.51 for self-reports to 0.66 for peer report measures. Although not reported here in detail, we found a similar increase from an average genetic influence of 0.51 for self-reports to 0.71 for peer reports for the three broad dimensions P, E, and N measured by the EPQ-RS (for details see Angleitner et al., 1997). The joint analysis of self- and peer reports yielded somewhat higher heritability estimates (0.75 on average) than those found for peer report data which is in agreement with the findings reported by Riemann et al. (1997). This is an interesting finding since the higher heritability estimates were not simply a result of the aggregation of self- and peer report data into a more reliable measure because error variance is controlled for in the peer report analyses as well. The joint analysis rather demonstrated that genetic influences determine the broad personality dimensions (constructs) measured by independent judgments. This finding implies that the covariance between self- and peer reports is largely due to shared genetic effects, which could be confirmed through the genetic and environmental correlations between self- and peer reports. Correlations of additive genetic effects were on average higher than 0.85. The analyses do not show meaningful differences between the three measured personality traits regarding genetic and environmental influences. Earlier studies sometimes report nonadditive effects for Neuroticism and Extraversion, which could be found in our study as well. Although there is no significant improvement compared to the more parsimonious model without nonadditive effects it should be borne in mind that nonadditive genetic effects might contribute to individual differences of personality. An assumption which should be tested in independent samples. 7. Conclusions We may conclude that the inclusion of peer reports in behavior genetic studies of personality provides a valuable tool. First, peer report data offer the opportunity to validate results from selfreport studies and second, the joint analyses of self- and peer report data facilitate––contrary to a concentration on personality measures––one to focus on broad personality constructs measured by independent judges. Acknowledgements Preliminary analyses of the data were presented at the 8th Meeting of the International Society for the Study of Individual Differences, Arhus, Denmark, July 19–23 and at the 11th European Conference on Personality, Jena, Germany, July 21–25. This research was supported in part by funds from the Max-Planck Forschungspreis (awarded by the Alexander von Humboldt Stiftung and the Max-Planck Gesellschaft) to Alois Angleitner and Jan Strelau. References Akaike, H. (1987). Factor analysis and AIC. Psychometrica, 52, 317–332. Angleitner, A., Riemann, R., & Strelau, J. (1997). Genetic and environmental influences on the EPQ-RS scales: A twin study using self- and peer reports. In Poster presented at the 8th Meeting of the International Society for the Study of Individual Differences, Arhus, Denmark.
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Ruch, W. (1999). Die revidierte Fassung des Eysenck Personality Questionnaire und die Konstruktion des deutschen EPQ-R bzw. EPQ-RK [Revised version of the Eysenck Personality Questionnaire and the construction of the German versions EPQ-R and EPQ-RK]. Zeitschrift f€ ur Differentielle und Diagnostische Psychologie, 20, 1–24. Schmitz, S., Cherny, S. S., & Fulker, D. W. (1998). Increase in power through multivariate analyses. Behavior Genetics, 28, 357–363. Shrout, K. J., & Fleiss, J. L. (1979). Intraclass correlation: Use in assessing rater reliability. Psychological Bulletin, 86, 420–428. Spinath, F. M., & Angleitner, A. (1998). Contrast effects in Buss and PlominÕs EAS questionnaire: a behavioral-genetic study on early developing personality traits assessed through parental ratings. Personality and Individual Differences, 25, 947–963. Spinath, F. M., Riemann, R., Hempel, S., Schlangen, B., Weiß, R., Borkenau, P., & Angleitner, A. (1999). A day in the life: description of the German Observational Study on Adult Twins (GOSAT) assessing twin similarity in controlled laboratory settings. In I. Mervielde, I. Deary, F. DeFruyt, & F. Ostendorf (Eds.), Personality psychology in Europe (Vol. 7). Tilburg: Tilburg University Press.
Genetic and environmental influences on the EPQ-RS scales: a twin study using self- and peer reports Heike Wolf a
a,*
, Alois Angleitner b, Frank M. Spinath b, Rainer Riemann a, Jan Strelau c
Friedrich-Schiller-Universit€at Jena, Department of Psychology, Humboldtstr. 26 D-00743, Jena, Germany b University of Bielefeld, Department of Psychology, P.O. Box 10 01 31, 33501 Bielefeld, Germany c University of Warsaw, Faculty of Psychology, ul. Stawki 517, PL-00183 Warsaw, Poland Received 6 March 2003; received in revised form 11 September 2003; accepted 29 September 2003 Available online 19 November 2003
Abstract We examined genetic and environmental influences on the scales of the German Eysenck Personality Questionnaire-RS (EPQ-RS) in a sample of 496 monozygotic, 181 same-sex, and 68 opposite-sex dizygotic adult twin pairs. Along with other questionnaires each participant completed the EPQ-RS and was also described by two independent peers on a peer report form of the EPQ-RS. Based on this design it was possible to analyse not only the standard univariate twin model but more powerful multivariate models to estimate the genetic and environmental sources of variance on phenotypic individual differences. Partly because latent variables are error free, the joint analyses of self- and peer report data yielded genetic contributions to phenotypic variance that were substantially higher than typically found in univariate analyses based on self-report data alone (h2 ¼ 0:67–0:86). These high genetic correlations between self- and peer reports provide evidence for the validity of personality ratings. Ó 2003 Elsevier Ltd. All rights reserved. Keywords: EPQ-RS; Personality; Twins; Genetics; Self- and peer reports
1. Introduction Behavior genetic research in the field of personality provides consistent evidence for a substantial genetic influence on major dimensions of personality (Bouchard, 1997; Eaves, Eysenck,
*
Corresponding author. Tel.: +49-36-41-94-51-63; fax: +49-36-41-94-51-62. E-mail address: [email protected] (H. Wolf).
0191-8869/$ - see front matter Ó 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2003.09.028
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& Martin, 1989). One of the most influential models in the field of personality focuses on three major personality factors, namely Psychoticism (P), Extraversion (E), and Neuroticism (N) (Eysenck & Eysenck, 1985). Numerous studies using the Eysenck Personality Questionnaire (EPQ; Eysenck & Eysenck, 1975) or related inventories measuring the PEN model found substantial genetic effects on all three of EysenckÕs personality factors, (e.g., Eaves et al., 1989; Martin & Jardine, 1986). A meta-analysis of early twin studies yielded heritability estimates (h2 ) for P, E, and N of 0.46, 0.58, and 0.44, respectively (Eaves et al., 1989). The authors report evidence from two large twin studies and one study of extended kinship. Heritability estimates fall between 0.40 and 0.53 for the three personality factors. Although these findings demonstrate substantial genetic influence on interindividual differences in personality, the magnitude of the estimates also indicate that environmental factors are equally important. However, this environmental influence is almost entirely of the nonshared environmental variety. Loehlin and Martin (2001) reported age trends in heritabilities of the Eysenck personality dimensions. Results of model-fitting for same-sex twin pairs in three age groups were in agreement with results from previous studies. For Extraversion and Neuroticism heritability estimates were 0.47 and 0.40, respectively. Merely for Psychoticism the heritability estimate of 0.28 was lower. Significant age differences in the genetic or environmental parameters could not be found for any of the three personality traits P, E, and N (Loehlin & Martin, 2001). In general, the data summarized here indicates substantial heritability for all the dimensions of the EPQ. Genetic factors explain about 50% of the variance in personality traits (Eysenck, 1990). On the other hand, environmental influences shared by siblings or twins contribute only marginally to personality differences (Bouchard, 1994; Eysenck, 1990). It is noteworthy that these conclusions for adult personality measures rely almost exclusively on self-reports. Because self-reports are known to be prone to particular biases, the inclusion of peer reports into behavior-genetic studies of personality provides a valuable extension of the traditional approach (Riemann, Angleitner, & Strelau, 1997). The assessment of peer report data allows a validation of the results from self-report studies. Furthermore, the inclusion of another source of data permits separating the influence of nonshared environmental effects from measurement error. As pointed out in previous studies (e.g. Borkenau, Riemann, Spinath, & Angleitner, 2000; Hofstee, 1994; Riemann et al., 1997) one shortcoming of self-report data is that such personality judgments do not directly reflect behavioral differences. Responses to questionnaire items or rating scales require inferences and interpretations. Thus, heritability coefficients or estimates of environmental influences might not only reflect content variance but also variance in individual response styles. Second, Borkenau et al. (2000) also argued that self-reports may be distorted by ‘‘contrast effects’’. These effects result in an underestimation of the similarity between DZ twins and may obscure shared environmental effects (Spinath & Angleitner, 1998). Contrast effects might arise from an exaggeration of real behavioral differences between twin siblings if twins compare their own behavior to the behavior of their co-twin rather than to the population average. It is also possible that MZ twins discount behavioral differences because of their generally high similarity. The use of peer reports in addition to self-reports is one way to overcome contrast effects, especially if peers judge only one twin of a pair. Ideally, information is gathered from peers who know only one of the twins very well and have little or no contact with the other twin sibling.
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The validity of peer reports in personality research has been widely demonstrated (Funder, 1987; Kenny, 1991, 1994). Peer reports consistently show substantial positive correlations both among each other and with self-report data (Funder & Colvin, 1997). In the study mentioned above (Riemann et al., 1997) self- and peer reports of the NEO FiveFactor Inventory (NEO-FFI; Costa & McCrae, 1989) were collected. The NEO-FFI is a standard inventory for the assessment of the dimensions of the Five-Factor model (Goldberg, 1993; John & Srivastava, 1999; McCrae & Costa, 1997) measuring the five broad personality factors Neuroticism, Extraversion, Openness to Experience, Conscientiousness, and Agreeableness. Analyses of the self-report data replicated earlier findings of a substantial genetic influence on the personality dimensions of the Five-Factor model with heritability estimates between 0.42 and 0.53 on all broad NEO-FFI dimensions. A similar pattern of results was found for peer reports yielding even higher heritability estimates, because measurement error was controlled for. Thus, Riemann et al. (1997) concluded that self-report studies of single personality measures tend to underestimate genetic influences because they do not allow the separation of error variance from variance due to specific environmental influences. Reconsidering the results of behavioral genetic self-report studies on the three factors of the Eysenckian personality model clearly displays great similarities to influences of genetic and environmental factors on the dimensions of the five-factor model. While Riemann et al. (1997) analyzed genetic and environmental influences on peer reports of the Five-Factor model, to our knowledge no study has reported similar analyses for the Eysenckian personality factors. Therefore, the present study is a continuation of the analyses of the genetic and environmental influences on the EPQ-RS scales based on self- and peer reports presented by Angleitner, Riemann, and Strelau (1997). The main purpose of this continuation is to estimate genetic and environmental influences on the dimensions of the EPQ-RS using self- and peer report data in joint analyses similar to the analyses presented by Riemann et al. (1997) on self- and peer report ratings of the NEO-FFI. The multivariate design provides the opportunity to estimate effects due to nonshared environmental influences on personality traits separately from measurement error. Thus, heritability estimates derived from multimethod sources of assessment are important to corroborate results from single modes of assessment. Furthermore, through the joint analyses of self- and peer report data it is possible to estimate genetic and environmental influences on broad personality traits (constructs) measured by independent judges. Finally, genetic and environmental correlations will be estimated between self- and peer report measures. The structure of these correlations provides information about genetic and environmental mediation of the covariance between self- and peer reports. Separate analyses of both data sources are valuable in that they can validate one another. However, a similar quantitative etiological estimate might still reflect qualitatively different influences. Joint analyses of self- and peer reports are required to address etiological sources of the covariation between traits or different modes of assessment directly.
2. Method The study presented is part of the Bielefeld–Warsaw Twin Project chaired by Alois Angleitner and Jan Strelau. From the total German sample we selected those participants who completed the
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questionnaires relevant for the present study. Thus, participants were 496 MZ twin pairs, 181 same-sex DZ twin pairs (DZss) and 68 opposite-sex DZ twin pairs (DZos). Their age varied between 17 and 83 years with a mean of 33.9 years (SD ¼ 13.0 years). Considering same-sex twin pairs, women (542 pairs) participated more frequently than men (135 pairs). Gender was not significantly associated with zygosity. All twin pairs were volunteers recruited through newspaper and media announcements. Zygosity was determined using a physical similarity questionnaire (Oniszczenko, Angleitner, Strelau, & Angert, 1993) in which participants were asked to describe and compare themselves with their co-twins on a number of physical characteristics. This questionnaire was validated in a subsample of 122 (84 MZ, 38 DZ) same-sex twin pairs by means of DNA analysis yielding a highly satisfying correct classification rate (93.6%). This is in good agreement with other studies assessing the validity of zygosity questionnaires (Lykken, 1978; Plomin, DeFries, & McClearn, 1990). Misclassifications were more likely to the effect that DZ twins were classified as monozygotic (6 cases) than classifying MZ twins as dizygotic (one case).
3. Measures All twin pairs completed a set of temperament and personality questionnaires at home (see Spinath et al., 1999; for a detailed overview of these sets). Among these measures were the selfand peer report versions of the German short form of the Revised Eysenck Personality Questionnaire (EPQ-RS: Eysenck & Eysenck, 1991; Ruch, 1999). The peer report version of the EPQRS was identical to the self-report version, except that the items were reformulated in the third person form. Participants were instructed to complete the questionnaires independently of one another in a nondistracting setting. In addition, each twin was asked to give the peer report versions of the questionnaires to two peers who preferably knew the respective twin but not the co-twin well. Subjects returned self- and peer reports by mail; to guarantee anonymity the latter were sealed by the peers in separate envelopes. The EPQ-RS was developed by Eysenck and Eysenck (1991) for the economic measurement of the dimensions Psychoticism (P), Extraversion (E), and Neuroticism (N). A control scale (Lie, L) is also included in the questionnaire. The original English version contains 48 items––12 items per scale. The German EPQ-RS (Ruch, 1999) comprises 50 items––14 items to measure P and 12 items for each of the three remaining scales. Psychometric properties of the German translation are good and similar to those of the original EPQ-RS (Ruch, 1999).
4. Analyses Prior to behavior genetic analyses, all scores were regressed on age and sex. This has become a standard procedure in twin research, particularly in samples covering a large age range because monozygotic and same-sex dizygotic pairs are perfectly correlated for gender and age, so any similarity between these twins will be spuriously increased if gender and age effects are present for the variable in question (McGue & Bouchard, 1984).
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Behavior genetic analyses were carried out only for the content scales of the EPQ-RS, that is Psychoticism, Extraversion, and Neuroticism, because the Lie scale was originally designed as a validity scale assessing the presence of response sets such as social naivete or conformity in the EPQ-R. In the present study, we did not analyse this scale because the status of the Lie scale as a personality trait remains unclear. Intraclass correlations (ICC 1.1; Shrout & Fleiss, 1979) were calculated as a measure of twin similarity for the three content scales separately for the self- and the peer report data. We used multivariate maximum-likelihood model fitting to estimate the influence of genetic and environmental sources of variance on phenotypic individual differences because multivariate designs have greater power to detect smaller genetic and environmental influences than univariate designs (Schmitz, Cherny, & Fulker, 1998). Note that for these analyses opposite-sex twin pairs were omitted because they are not as comparable to MZ twin pairs. Given that the present study assessed self- and peer reports, a multivariate model including three different raters (one self- and two peer reports) per target person can be fitted to the data. The joint analysis of self- and peer report data also yields estimates separately interpretable for self- and peer reports which are comparable to separate univariate analyses. Self- and averaged peer report data was analysed simultaneously using the computer program Mx (Neale, Boker, Xie, & Maes, 1999) to estimate genetic and environmental influences on the latent phenotype independently of possible rater bias and unreliability of the ratings. The analyses were based on variance-covariance matrices. Our models specified additive genetic effects (A), genetic dominance effects (D), shared environmental effects (C), and nonshared environmental effects (E). In analyses based exclusively on self-report data (not reported in the present study), E is a confound of variance due to nonshared environmental effects and measurement error. In multivariate analyses error variance can be separated from nonshared environmental variance. Genetic dominance and shared environmental effects were fitted alternatively. The models were systematically modified to drop A, D or C and E effects to test their significance. The fit criteria used to determine the ‘‘best-fitting’’ model were chi-square differences, the principle of parsimony and root mean square error of approximation. Overall goodness-of-fit was assessed with v2 and AkaikeÕs Information criterion (Akaike, 1987: AIC ¼ v2 2df). The AIC was used to decide between (unnested) models that both fitted the data according to the chi-square criterion. The models fitted to our data are depicted in Fig. 1. Model 1––the latent factor model with method effects––is based on the rater bias model described by Neale and Cardon (1992). Although self- and peer reports were provided by different judges for each twin, method factors were included in the model because the similarity among selfand among peer ratings, even if they stem from different persons, may be greater than the similarity between self- and peer ratings. Model 2 is more parsimonious than model 1 since it does not include method factors. Due to the availability of self- and peer reports it is possible to perform bivariate analyses to estimate genetic (rG ), shared (rC ), and nonshared (rE ) environmental correlations which estimate the extent to which two variables share genetic, shared or nonshared environmental variance (Fig. 2). Although in standard bivariate behavioral genetic analyses, rG , rC , and rE are estimated to explain the covariation between different traits, it is also informative to estimate the extent to which genetic or environmental factors contribute to the observed correlation between methods,
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H. Wolf et al. / Personality and Individual Differences 37 (2004) 579–590 MZ r=1.0/DZ r=.25 r=1.0
C
D E
A
MZ r=1.0/ DZ r=.5
C
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2
3
2 1
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4
E 4
P Tw1
P Tw2
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6
R s1
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R p1 9
8 R s2
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R p2 10
Bs
(a)
Av. Peer Tw2
Self Tw2
8
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Self Tw1
D 3
Bp
MZ r=1.0/DZ r=.25 r=1.0
C
D E
3
A
MZ r=1.0/ DZ r=.5
C
A
2
2 1
1
4
Self Tw1
P Tw2 6
5
Av. Peer Tw1
8
7
(b)
R s1
E
3 4
P Tw1 5
D
R p1
Self Tw2
7
Av. Peer Tw2
8 R s2
R p2
Fig. 1. Latent factor models with and without method effects for the joint analysis of self- and peer report data. (a) Latent factor model with method effects (rater bias model) for the joint analysis of self- and peer report data and (b) latent factor model without method effects for the joint analysis of self- and peer report data. Note: (a) The variance of the phenotypic trait was constrained to unity. Paths 5 and 6 and paths 7 and 8 were constrained to be equal for twins and co-twins as well as for MZ and DZ twins. Paths 9 and 10 were estimated for each method (self- vs. peer report) separately. They were constrained to be equal within methods and between MZ and DZ twin groups. A ¼ additive genetic effects; C ¼ shared environmental influences; D ¼ genetic dominance effects; E ¼ specific environmental influences; P Tw1 and P Tw2 ¼ phenotype of twin 1 or 2; self Tw1 and Self Tw2 ¼ self-report of twin 1 or 2; av. peer Tw1 and av. peer Tw2 ¼ peer report (averaged across two raters) on twin 1 or 2; BS ¼ method effects for self-reports; BP ¼ method effects for peer reports; RS and RP ¼ measures error variance.
for example, self- and peer reports. Bivariate rG , rC , and rE are estimated by fitting a structural equation model known as ‘‘Cholesky decomposition’’ (see Neale & Cardon, 1992) using the computer program Mx (Neale et al., 1999). In addition to rG , rC , and rE it is also informative to compute the proportion of the phenotypic correlation between self- and peer reports that is mediated by either genetic or environmental influences. This proportion can not be derived directly from the genetic and environmental correlation alone as it depends in part on the estimates of genetic and environmental influences from the univariate or in this case multivariate analyses of self- and averaged peer report data (Loehlin, 1996).
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rE rC rG E
C
eS
cS
A
A
C
eP
aS
Selfreport
cP
E
aP
av. Peer report
Fig. 2. Simplified correlated factors model for the analysis of the etiology of the relation between self- and peer reported personality. Note: See text for description of the model. A ¼ additive genetic effects; C ¼ shared environmental influences; E ¼ specific environmental influences; as , cs and es ¼ additive genetic, shared and nonshared environmental influences on self-reported personality; ap , cp and ep ¼ additive genetic, shared and nonshared environmental influences on peer reported personality; rG ¼ genetic correlation; rC ¼ shared environmental correlation; rE ¼ nonshared environmental correlation.
5. Results Internal consistencies (coefficient alphas) of the EPQ-RS self- and peer report scales ranged from 0.59 to 0.84 (mean 0.74) for self-reports and from 0.67 to 0.86 (mean 0.77) for peer reports. For all scales, internal consistencies were marginally higher for the peer report data. For both ratings (self- and peer reports), internal consistencies were lowest for Psychoticism. The two peer raters showed a satisfactory agreement of 0.57 on average. Correlations between self-reports and averaged peer reports were in the range of 0.47 to 0.82 (mean 0.68), indicating high validity for the self- and peer report measures. Twin similarities (ICC 1.1) for the EPQ-RS scales are given in Table 1 for the self- as well as for the peer report data. Table 1 Intraclass correlations (ICC 1,1) of the EPQ-RS self- and averaged peer report scales for MZ and DZ twins MZ (N ¼ 496)
DZss (N ¼ 181)
DZos (N ¼ 68)
Self-reports Psychoticism Extraversion Neuroticism
0.44 0.57 0.56
0.23 0.20 0.11
0.19 0.18 )0.07
Mean
0.53
0.18
0.10
Peer reports Psychoticism Extraversion Neuroticism
0.43 0.47 0.36
0.27 0.19 0.26
0.19 0.19 0.07
Mean
0.42
0.24
0.15
Note: Statistics are based on scores corrected for age and gender effects.
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Similarity correlations for MZ twins exceeded those of DZ twins for all scales regardless of the method used (self- or peer reports). For self-reported Extraversion and Neuroticism, the magnitude of the MZ twins correlations was greater than twice the similarity of the DZ twins. This pattern was replicated through peer reports for one of the two scales, namely Extraversion, indicating that a proportion of the overall or broad genetic influence might be due to nonadditive genetic effects. Goodness-of-fit statistics and parameter estimates from the multivariate analyses for the EPQRS scales with and without method factors are displayed in Table 2. As described above, we first tested a latent factor model with method effects (rater bias model). Overall, the reduced AE model yielded an appropriate fit to the data for all three scales. The inclusion of shared environmental variance improved the fit for Psychoticism only marginally (v2 difference ¼ 0.76, df ¼ 1, ns). For Extraversion, the ACE model was rejected at the 0.05 level. Allowing for genetic dominance did not improve the fit significantly compared to the more parsimonious AE model (v2 difference ¼ 1.67, df ¼ 1, ns). For all scales and regardless of the inclusion or exclusion of method factors, a model without genetic factors (CE and E) was rejected. For Neuroticism, genetic dominance was an important source of variance. The inclusion of D improved the fit significantly (v2 difference ¼ 4.61, df ¼ 1, p < 0:05). However, fitting an ADE model for the Neuroticism data resulted in a parameter estimate of zero for additive genetic variance. Hence, a reduced DE model yielded the same fit. Because the existence of genetic dominance effects without influences of additive genetic variance is considered to be unlikely (Roberts, 1967), we decided to favor the AE model as a parsimonious and theoretically coherent alternative. For Extraversion and Neuroticism the model with method factors fitted the data significantly better than the model without method factors although the estimated method effects for Extraversion were small. For Psychoticism there was no significant difference in model fit between the model with and the model without method factors. Repeating the analyses with raw data yielded virtually identical results. Table 2 Model-fitting results for the joint analyses of self- and peer report data with and without method factors Model fit v2
Fit indices RMSEA
a2
d2
e2
b2s
b2p
Latent factor model with method effects P AE 12.00 13 0.53 E AE 15.20 13 0.30 N ADE 13.81 12 0.31 AE 18.42 13 0.14
0.000 0.023 0.018 0.028
0.82 0.67 0.66 0.00
– – 0.68 –
0.18 0.34 0.32 0.33
0.03 0.00 0.00 0.00
0.04 0.06 0.15 0.15
Latent factor model without P AE 14.63 E AE 24.16 N ADE 39.57 AE 43.38
0.010 0.025 0.063 0.070
0.86 0.68 0.00 0.74
– – 0.74 –
0.14 0.32 0.26 0.26
– – – –
– – – –
df
p
method effects 15 0.48 15 0.06 14 0.00 15 0.00
Note: The analyses are based on age- and sex-corrected data from 496 MZ and 181 same-sex DZ twin pairs. See text for description of the models. P ¼ psychoticism; E ¼ extraversion; N ¼ neuroticism; A ¼ additive genetic effects; E ¼ specific environmental effects and error influences; D ¼ genetic dominance effects. b2s ¼ parameter estimates for the methodeffects due to self-reports; b2p ¼ parameter estimates for the method-effects due to peer reports. df ¼ degrees of freedom.
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Table 3 Results from bivariate model-fitting analyses for self- and peer reported EPQ-RS scales P E N
v2
p (df ¼ 14)
rG
rE
rG c
rE c
11.65 12.35 20.71
0.63 0.58 0.11
0.90 [0.80; 1.00] 0.91 [0.85; 0.96] 0.76 [0.67; 0.85]
0.15 [0.07; 0.23] 0.48 [0.42; 0.55] 0.31 [0.23; 0.38]
0.82 0.66 0.67
0.18 0.34 0.33
Note: The analyses are based on age- and sex-corrected data from 496 MZ and 181 same-sex DZ twin pairs. P ¼ psychoticism; E ¼ extraversion; N ¼ neuroticism; rG ¼ genetic correlation, rE ¼ nonshared environmental correlation, rG c ¼ proportion of the phenotypic correlation due to genetic mediation, rE c ¼ proportion of the phenotypic correlation due to nonshared environmental mediation. Confidence intervals (95%) for rG and rE are provided in brackets.
Table 3 shows the results from bivariate model fitting analyses of self- and peer reports on the EPQ-RS scales. An AE model fitted the data best. Genetic correlations ranged from 0.76 for Neuroticism to 0.91 for Extraversion. Environmental correlations were substantially smaller. The two rightmost columns of Table 3 present the proportions of the phenotypic correlations that are mediated by genetic or environmental influences. As can be seen, for all scales the major proportion of the phenotypic correlation was due to genetic mediation ranging from 67% for Neuroticism to 82% for Psychoticism. 6. Discussion The present study investigated the etiology of the Eysenckian personality traits in a multimethodological way. Apart from self-reports of personality each twin was described by two peers on peer-report versions of the same questionnaires. Thus, on the one hand, the present study could be viewed as a replication study. The analyses of the self-report data support earlier findings (e.g., Eaves et al., 1989; Martin & Jardine, 1986) of substantial genetic influences on all broad personality dimensions. Consistent differences between the three broad scales are hardly noticeable across studies. The present study found MZ correlations between 0.44 and 0.57 and same-sex DZ correlations between 0.11 and 0.23, which are comparable to results reported by Bouchard (1997). In the group of opposite-sex DZ twins we found an insignificant negative correlation (rDZos ¼ 0:07) for Neuroticism which could be due to contrast effects (Spinath & Angleitner, 1998) but could also be due to differences in the etiology of Neuroticism between males and females. Analyses of the peer report data in the present study clearly demonstrated family resemblance for the three personality dimensions with MZ twin correlations between 0.36 and 0.47 and samesex DZ twin correlations between 0.19 and 0.27. Thus, a comparison of the results for self-report and peer report data across the EPQ-RS scales displayed substantial similarity. Estimating genetic and environmental influences on the basis of peer report measures represents an advantage compared to estimates on the basis of self-report measures alone because the analyses of a latent variable with loadings from the two peer reports per twin allows the separation of error variance from nonshared environmental influences. Estimates of genetic influences derived from peer report data were found to be somewhat higher than from self-reports. For example, Riemann et al.
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(1997) who measured the Big Five traits by the German version of the NEO-FFI found an increase in the averaged estimates of genetic influences from 0.51 for self-reports to 0.66 for peer report measures. Although not reported here in detail, we found a similar increase from an average genetic influence of 0.51 for self-reports to 0.71 for peer reports for the three broad dimensions P, E, and N measured by the EPQ-RS (for details see Angleitner et al., 1997). The joint analysis of self- and peer reports yielded somewhat higher heritability estimates (0.75 on average) than those found for peer report data which is in agreement with the findings reported by Riemann et al. (1997). This is an interesting finding since the higher heritability estimates were not simply a result of the aggregation of self- and peer report data into a more reliable measure because error variance is controlled for in the peer report analyses as well. The joint analysis rather demonstrated that genetic influences determine the broad personality dimensions (constructs) measured by independent judgments. This finding implies that the covariance between self- and peer reports is largely due to shared genetic effects, which could be confirmed through the genetic and environmental correlations between self- and peer reports. Correlations of additive genetic effects were on average higher than 0.85. The analyses do not show meaningful differences between the three measured personality traits regarding genetic and environmental influences. Earlier studies sometimes report nonadditive effects for Neuroticism and Extraversion, which could be found in our study as well. Although there is no significant improvement compared to the more parsimonious model without nonadditive effects it should be borne in mind that nonadditive genetic effects might contribute to individual differences of personality. An assumption which should be tested in independent samples. 7. Conclusions We may conclude that the inclusion of peer reports in behavior genetic studies of personality provides a valuable tool. First, peer report data offer the opportunity to validate results from selfreport studies and second, the joint analyses of self- and peer report data facilitate––contrary to a concentration on personality measures––one to focus on broad personality constructs measured by independent judges. Acknowledgements Preliminary analyses of the data were presented at the 8th Meeting of the International Society for the Study of Individual Differences, Arhus, Denmark, July 19–23 and at the 11th European Conference on Personality, Jena, Germany, July 21–25. This research was supported in part by funds from the Max-Planck Forschungspreis (awarded by the Alexander von Humboldt Stiftung and the Max-Planck Gesellschaft) to Alois Angleitner and Jan Strelau. References Akaike, H. (1987). Factor analysis and AIC. Psychometrica, 52, 317–332. Angleitner, A., Riemann, R., & Strelau, J. (1997). Genetic and environmental influences on the EPQ-RS scales: A twin study using self- and peer reports. In Poster presented at the 8th Meeting of the International Society for the Study of Individual Differences, Arhus, Denmark.
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