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The General Factor of Personality and peer-rated social status: A rejoinder to de Vries (2011)
Personality and Individual Differences 51 (2011) 836–839
Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
The General Factor of Personality and peer-rated social status: A rejoinder to de Vries (2011) Dimitri van der Linden ⇑ Institute of Psychology, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands
a r t i c l e
i n f o
Article history: Received 25 January 2011 Received in revised form 5 July 2011 Accepted 10 July 2011 Available online 6 August 2011 Keywords: Big Five General Factor of Personality Social status
a b s t r a c t In a previous study we showed that self-reported Big Five scores and the General Factor of Personality (GFP) were related to peer-ratings of likeability and popularity (van der Linden, Scholte, et al., 2010). de Vries (2011a) re-analyzed our data and concluded that (i) there was no evidence of a GFP, and (ii) the GFP we used was latent factor of Extraversion. In this rejoinder I present arguments that compromise the re-analysis and conclusions as described by de Vries (2011a) and emphasize the relevance of the GFP. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Recently, Personality and Individual Differences published an article of de Vries (2011a) who discussed our study on personality and social status (van der Linden, Scholte, Cillessen, te Nijenhuis, & Segers, 2010). de Vries re-analyzed the data as described in our article and questioned our conclusions about the General Factor of Personality (GFP). In the present paper, I will reply to the findings of de Vries (2011a) and present arguments to support the conclusions that we described in our 2010 paper. In order to provide a context for this reply, I will first give a short overview of the van der Linden, Scholte, et al. (2010) study and of the re-analysis as described in de Vries (2011a). In the van der Linden, Scholte, et al. (2010) study, 512 high school classmates (Mage = 14.8 years) from 22 different classes could freely nominate classmates on a range of social status questions. This sociometric approach provided information about the likeability and popularity of the participants. We also had access to students’ self-reports of personality as assessed with the Quick Big Five (QBF) questionnaire (Vermulst & Gerris, 2005). The van der Linden et al. article contained two main messages. The first was that self-reported Big Five factors were related to peer-ratings. Particularly Extraversion and Emotional Stability were positively related to likeability and popularity. Agreeableness was positively related to likeability and Conscientiousness was negatively related to popularity. These findings are relevant because currently only few studies have examined the relationship between self-reported personality and sociometric measures of social status. ⇑ Tel.: +31 10 408 2454; fax: +31 10 408 9009. E-mail address: [email protected] 0191-8869/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2011.07.010
The second message in the van der Linden, Scholte, et al. (2010) article was that likeability and popularity were related to the GFP. The GFP is a topic that is receiving increasing attention in the literature and several researchers assume that this general factor occupies the apex of the hierarchical structure of personality (e.g., Musek, 2007; Rushton & Irwing, 2011). The evidence that a GFP exists in many personality measures is indisputable (Rushton & Irwing, 2011; van der Linden, te Nijenhuis, & Bakker, 2010). Nevertheless, there is an ongoing debate about the nature of this construct. Several researchers have suggested that the GFP may be a substantive factor with theoretical implications (Figueredo et al., 2005; Rushton & Irwing, 2011). However, others have suggested that the GFP may not be much more than a statistical and methodological artifact (e.g., Anusic, Schimmack, Pinkus, & Lockwood, 2009). In previous studies, the GFP has been operationalized as the first unrotated factor in personality measures or as a latent factor using Confirmatory Factor Analysis (CFA) or Structural Equation Modeling (SEM). In the van der Linden, Scholte, et al. (2010) study we used both methods to show that the GFP was positively related to likeability as well as popularity. We argued that this finding has implications for the substantive versus artifact debate because if the GFP would only be a measurement artifact it is not clear why it would relate to peer-ratings of social status. So, in our study we suggested that the GFP may indeed reflect a substantive personality factor that affects how classmates perceive each other. From his recent article, it can be inferred that de Vries (2011a) agrees with our findings on the associations between the Big Five and social status; his critique mainly focuses on our findings regarding the GFP. More specifically, de Vries re-analyzed our study correlation matrix and concluded that the data does not provide evidence for a GFP. This conclusion was mainly based on two
D. van der Linden / Personality and Individual Differences 51 (2011) 836–839
findings. First, de Vries constructed an alternative CFA/SEM model without an explicit GFP, but with an equal number of degrees of freedom that showed a better fit than our original GFP model. Second, in regression analyses, the GFP did not predict social status beyond Extraversion (for details see de Vries, 2011a). In the present reply, I describe several limitations in the argumentation and re-analyses of de Vries (2011a) re-emphasize the relevance of our previous findings for GFP research. 2. The GFP model versus alternative models In his paper, de Vries constructed an alternative CFA/SEM model (see Figure 2, de Vries, 2011a, p. 514) without a GFP and in which only Extraversion positively related to likeability (.37) and popularity (.32). Based on several fit indices de Vries concluded that although the original GFP model had an acceptable fit, the alternative model has a better fit. I do not question this finding. Yet, to understand the limitations of this alternative model it is important to note that the major criteria to establish good CFA/SEM models are (i) to provide the best possible reproduction of the sample correlation matrix, which can be relatively easy, for example by including many correlated errors, but also (ii) to provide a solution that is in accordance with a thorough theoretical account of the model (Barrett, 2007). This latter criterion is more difficult to fulfill than the former. In my view, an important limitation of de Vries’ (2011a) model is that the second criterion of the CFA/SEM approach was not met. Specifically, de Vries included several correlated errors between the Big Five factors without providing an explanation for them. So, he simply eliminated the paths between the Big Five factors and the GFP in the original model and re-modeled these substantive paths as correlated errors. In addition, he added two new correlated errors. Obviously, the model fit might increase in that way because the sample correlation matrix will be better represented. Nevertheless, this model also leads to additional conceptual problems. For example, taking away the GFP from a model but still allowing for relevant correlations between the lower-order personality factors can be considered a superficial method that relieves the researcher from providing theoretical explanations about why the factors are correlated in the first place. For example, de Vries based his choice for correlated errors on validation data of the Quick Big Five (Vermulst & Gerris, 2005) questionnaire (N = 19,907). In that data, Extraversion was still substantially related to Openness (.41), Agreeableness (.23), and Emotional Stability (.14). Agreeableness was related to Openness (.44) and Conscientiousness (.33). Thus, one major problem with the de Vries’ alternative model is that it still allows for correlations between factors that are theoretically unaccounted for. In contrast, models that contain a GFP provide at least an explanation for such correlations, namely that they are caused by an underlying mechanism that pushes lower-order traits towards the socially desirable end of the scale. Currently, the search on what this mechanism might be is ongoing. I will not elaborate on this in the present reply but I wish to mention that a good candidate for explaining this mechanism that has been described in the literature is emotional intelligence (Petrides et al., 2010). A final remark in this context is that in the debate about the GFP, different statistical models should be based on the different theoretical accounts that exist in this area. This would imply that in the GFP debate the alternative models to be tested against each other should contain higher-order factors (from factor intercorrelations) versus models that assume independent factors. 3. Is it only Extraversion? The other major argument in the de Vries article is that the GFP as described in van der Linden, Scholte, et al. (2010) represents
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nothing more than a latent Extraversion factor. This argument was based on the fact that the loading of Extraversion on the GFP was relatively strong, namely .79 in the factor analysis (Principal Factoring) and .84 in the CFA/SEM model. The loadings of the other factors were lower (.45, .40, and .30, for ES, A, and O, respectively) and Conscientiousness did not load on the GFP. There is no doubt that the GFP-factor loadings in this specific study partly compromised the sample-based GFP as a well-balanced mix of traits. Nevertheless, there are arguments that support that the GFP variable in van der Linden et al. is a relatively good marker of the GFP as described in previous studies. For example, in addition to constructing a GFP based on sample loadings van der Linden, Scholte, et al. (2010) also constructed a GFP based on meta-analytic loadings, using the 212 studies and 144,117 participants as reported in van der Linden, te Nijenhuis, et al. (2010). These meta-analytic loadings were .42, .63, .57, .57, and .62, for O, C, E, A, and ES, respectively. A GFP based on these loadings can truly be considered a balanced mix of all Big Five factors. The meta-analytic based GFP correlated no less than .86 with the sample-based GFP (van der Linden, Scholte, et al., 2010, p. 670). If the GFP would only represent a latent Extraversion factor it is unclear why it is so highly correlated with a variable that is made up of all the Big Five factors. In his article, de Vries does not refer to this important finding. Another argument against the notion of the GFP as a pure latent Extraversion factor is that even in the re-analysis of de Vries, Extraversion still shared a significant proportion of its variance with other Big Five factors: In the van der Linden et al. sample it mainly overlapped with Emotional Stability (r = .42), Agreeableness (r = .31), and Openness (r = .17). The latter two factors were also related to several other Big Five factors. The only trait that showed a deviating value in that sample was Conscientiousness with a correlation of r = .07 with Extraversion. So, even though Extraversion showed the strongest loading on the GFP, the Extraversion score itself consisted of a mix of different measures. The fact that Extraversion was not independent from other traits was acknowledged in the alternative CFA/SEM model of de Vries because he allowed this construct to correlate with three of the four remaining Big Five factors. de Vries also conducted separate regression analyses with likeability and popularity as dependent variables in which he entered Extraversion in the first step and the GFP in the second step. These analyses showed that Extraversion explained the largest part of the variance and adding the GFP in the second step led to only small increases in explained variance. In my view, these analyses mainly confirmed what we already knew before, namely that in our sample Extraversion had a strong GFP loading. Nevertheless, I wish to emphasize again that Extraversion itself was partly a mix of different Big Five measures. This finding can be compared to findings from the general cognitive ability factor g. In testing whether g can predict an outcome measure, say job performance, one can also use regression analyses. However, when g is entered in a regression after one has entered the score of the subtest with the highest gloading (for example a score on a reasoning subtest), then the contribution of g might be modest or even disappear. The reason for this is that g is strongly present in the specific subtest in the battery. So, in fact one tests for the effect of g after controlling for g. In line with the idea of a general factor, the appropriate analysis would be to test the extent to which the unique variance of the Big Five contributes to predicting relevant outcome variables after controlling for the GFP. This analysis is reported in the van der Linden, Scholte, et al. (2010) study. An alternative would be to test whether the GFP contributes to predicting the outcome variables (i.e., likeability, popularity) after controlling for the unique variance of the Big Five. The results of such a test would be nearly identical to the regression analysis as described in van der Linden, Scholte, et al. (2010). Specifically, I conducted the analyses with likeability
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and popularity as dependent variables and with the unique variance of the Big Five in the first step of a regression analysis and the GFP in step 2. In these analyses, the total unique variance of the Big Five explained a significant 4% of the variance in likeability and 9% in popularity. The GFP in step 2 contributed a significant 10% of the variance in likeability and 8% of popularity. In sum, it is apparent that in the van der Linden et al. study Extraversion showed the strongest association with social status. This is consistent with previous studies on personality and popularity (e.g., Anderson, John, Keltner, & Kring, 2001). However, GFP theory assumes that individual personality traits consist of unique variance plus a proportion of variance that is shared with other personality traits. The van der Linden, Scholte, et al. (2010) study indicated that the unique variance of several Big Five factors as well as their proportion of variance shared with other traits, i.e. the GFP, were related to social status.
4. The low Conscientiousness loading de Vries (2011a) mentioned that in the van der Linden, Scholte, et al. (2010) study, the specific loading of Conscientiousness on the GFP was low, which is in contrast with the findings of a large metaanalysis that found a mean Conscientiousness-GFP loading of .63 (van der Linden, te Nijenhuis, et al., 2010). Thus, a relevant question is how to interpret the low loading of Conscientiousness in the van der Linden, Scholte, et al. (2010) study. One way to address this question is in terms of measurement or sampling variability. For example, some studies have found that Conscientiousness was significantly related to social status in adolescents (e.g., Jensen-Campbell & Malcolm, 2007), whereas other studies found it was not (e.g., Anderson et al., 2001). A possible explanation for such discrepancies is that different measures of the Big Five may focus on different aspects of the traits. Conscientiousness, for instance, consists of aspects such as showing integrity, being reliable, working hard, and working carefully. From GFP theory it can be inferred that not all aspects of Conscientiousness have to be strongly related to the general factor. It can be expected that the magnitude of the GFP loadings of specific personality measures depends on the extent to which they contain aspects of social desirability (see also: Bäckström, Björklund, & Larsson, 2009). This idea fits with the hypothesis that the GFP is a mechanism that has a unidirectional influence on many personality traits, namely towards higher social desirability (Rushton & Irwing, 2011). Regarding this, it is important to note that in the Quick Big Five measure as used in van der Linden, Scholte, et al. (2010), particularly the ‘working carefully’ aspect of Conscientiousness was measured. This becomes apparent in the six Conscientiousness items, which are ‘careful’, ‘orderly’, ‘neat’, ‘accurate’, ‘systematic’, and ‘disorganized’ (reversely coded). Although further research is necessary, it is plausible that for adolescents these aspects of personality are not necessarily socially desirable in the sense that they are helpful in order to gain friends, a partner, or social recognition. As such, it would not be unusual that the GFP-loading of this scale is low. Beyond looking at the different aspects of Conscientiousness, there may be more general reasons to suggest that it may not be very relevant to focus on the low GFP-loading of one specific trait in one sample. More specifically, recently Pace and Brannick (2010) and Barrett and Rolland (2009) argued that in the various instruments and samples there is large variability in the characteristics of the Big Five. Barrett and Rolland (2009) looked at the correlations between Conscientiousness and Emotional Stability in nine published meta-analyses and found that these correlations ranged from .17 to .70. They argued that such findings require serious attention to the stability of personality measures. I agree with
Barrett and Rolland (2009) and with Pace and Brannick (2010) that the Big Five characteristics, including their intercorrelations, show strong variability. In our own meta-analysis on the Big Five intercorrelations (van der Linden, te Nijenhuis, et al., 2010) we also found wide ranges of intercorrelations between traits. For example, between the individual studies in the meta-analysis, the correlation between Conscientiousness and Extraversion ranged from from .20 (based on a N = 2901) to .61 (based on a N = 1054). Other Big Five intercorrelations showed similar levels of variability. Levels of variability as reported above are not what one would expect if one considers the Big Five as relatively clearly defined and stable constructs. Yet, such large variability exists and can be found in published and peer-reviewed articles that have mainly used well-known and validated instruments. The point of this is that large variability in personality measurement may need attention, but in any case would be a general issue in personality research and not specifically related to the GFP. Consequently, for the broader theory of the GFP it may not be very useful to give much attention to an occasional low loading of a specific trait. Regarding this, a relevant observation is that despite the variability in Big Five intercorrelations, the higher-order factors that emerge from them may be quite stable. For example, in a recent study (N 21.000) we showed that the GFPs derived from six different personality measures substantially overlapped, with a mean correlation of r = .53 and a range from .40 to .67 (van der Linden, te Nijenhuis, Cremer, & van der Ven, 2011). Some of these measures were based on the Big Five model (e.g., the NEO-PI-R) and others were not (e.g., Guilford Temperament Survey). In addition, Rushton et al. (2009) reported a correlation of .72 between the GFPs from the Tridimensional Personality Questionnaire (TPQ) and the NEO. Loehlin and Martin (2011) reported correlations ranging from .75 to .80 between measures based on Cloninger’s personality model (TPQ) and Eysenck’s model (EPQ). Finally, Rushton and Irwing (2011) reported Confirmatory Factor Analyses results from four personality questionnaires showing that the GFPs from these measures are nearly identical. Compared to this rather consistent set of findings from different studies, the only study that reported deviant results and did not find a strong relationship between GFPs from different measures was the one of de Vries (2011b) who used questionnaires based on the Big Five and the HEXACO model.
5. GFP research: some general issues The questions that de Vries raised about the GFP specifically relate to the study of van der Linden, Scholte, et al. (2010), but from the arguments I provided above it may be clear that they also relate to more general points in GFP research, namely about consistency and sample fluctuations of the construct. Although de Vries questioned the presence of the GFP in our study, it cannot be denied that in the majority of Big Five or other personality measures there is a common factor that reflects social desirability. In fact, this factor has been known for decades and has also been shown in numerous more recent studies (Loehlin & Martin, 2011; Musek, 2007; Rushton & Irwing, 2011; van der Linden, te Nijenhuis, et al., 2010). Consequently, the GFP debate does not focus on whether such a factor exists but on its interpretation. Proponents of the GFP suggest that it reflects social desirability in a true sense, implying that it may have relevance for many life areas such as job performance, social behavior, and psychological and somatic health (Figueredo et al., 2005). Several studies that looked at the genetics of personality traits suggest that the GFP has a relevant genetic component, which provides additional support for the substantive account of the general factor (e.g., Loehlin & Martin, 2011; Rushton et al., 2009). The majority of the GFP opponents would agree that the construct reflects social
D. van der Linden / Personality and Individual Differences 51 (2011) 836–839
desirability, but more in terms of response bias or measurement artifact (Anusic et al., 2009; de Vries, 2011b). Although this social desirability factor that is referred to as the GFP is relatively consistent over samples and measures, there is nevertheless sample fluctuation. For example, in a minority of samples one or more lower-level personality traits sometimes show relatively modest to low loadings on the GFP. Also, individual personality scales may sometimes show different loadings on different GFPs. For example, in the study of Loehlin and Martin (2011) the GFP in an adult sample displayed different factor loadings than the GFP from an adolescent sample, even though the same questionnaire was used in both samples (The EPQ). It currently remains an open question whether such variability is due to random sampling error, reflects systematic differences between samples, or is due to other reasons. Yet, it is unrealistic to expect that in each and every sample, the GFP is perfectly represented. Consequently, it is also unrealistic to require that in every individual sample the GFP will fulfill the strictest of criteria to show its existence (e.g., optimal model fit, maximum likelihood). This would be just as harsh as requiring that in each and every individual sample that uses the Big Five (or any other personality model) there is an empirical confirmation of that model. For example, that in every study items should load on the designated dimensions and that intercorrelations between the Big Five are identical from one study to the other. It is obvious that such confirmation will not be found in many studies, but that does not compromise the relevance of the Big Five. In the light of this, it is clear that the GFP in the van der Linden, Scholte, et al. (2010) study had some limitations. This was acknowledged by the authors (p. 672). Nevertheless, in the arguments described above I argue that the factor that was extracted was more than a latent factor of one single Big Five dimension but reflected the shared variance. This shared variance points into the direction of a more general social desirable tendency involving sociability, kindness, and a propensity to experience a stable and positive mood. The GFP that was extracted from the sample loadings showed a strong overlap (r = .86) with a GFP that was based on stable, meta-analytic loadings. Such a finding would not be expected if the GFP in the van der Linden, Scholte, et al. (2010) study would merely reflect a single Big Five factor. Instead the overlap between GFPs supports the idea of a general factor. Finally, the sample-based as well as the meta-analytically based GFPs showed associations with peer ratings of likeability and popularity. As a final remark, it is important to note that in the social sciences no single study can confirm or disconfirm a specific theory. This may be even more so in an area such as personality research where the various measures of presumed identical constructs sometimes show considerable variability. A good approach would be to increase knowledge by discovering general trends over a large number of different studies, each with their limitations. Some individual studies will make a strong case in favor of or against a specific theory; other will make a more modest contribution. Further, it is important to acknowledge that factor analytic techniques have several limitations. For example, Krijnen (2004) argued that any matrix with positive elements allows the extraction of a general factor. That statistical phenomenon in itself does not necessar-
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ily provide useful information about the nature or the consistency of such a factor. In addition, factor analytic techniques are not sufficient to establish causal relationships. In order to test whether the GFP indeed reflects an underlying construct affecting personality traits, it would be useful to collect data that may reveal causal effects of the GFP on lower-order traits as well as of the GFP on other relevant outcome variables such as health and social functioning. Longitudinal or experimental studies may be a way to collect such data. Thus, different types of studies are required to form a coherent picture on the viability and theoretical relevance of the GFP. References Anderson, C., John, O. P., Keltner, D., & Kring, A. M. (2001). Who attains social status? Effects of personality and attractiveness in social groups. Journal of Personality and Social Psychology, 81, 116–132. Anusic, I., Schimmack, U., Pinkus, R. T., & Lockwood, P. (2009). The nature and structure of correlations among Big Five ratings: The Halo-Alpha-Beta model. Journal of Personality and Social Psychology, 97, 1142–1156. Bäckström, M., Björklund, F., & Larsson, M. R. (2009). Five-factor inventories have a major general factor related to social desirability which can be reduced by framing items neutrally. Journal of Research in Personality, 43, 335–344. Barrett, P. (2007). Structural equation modeling: Adjudging model fit. Personality and Individual Differences, 42, 815–824. Barrett, P., & Rolland, J. P. (2009). The meta-analytic correlation between two Big Five factors: Something is not quite right in the woodshed. The Strategic White paper Series. http://pbarrett.net/stratpapers/metacorr.pdf. de Vries, R. E. (2011a). No support for a general factor of personality in a reanalysis of Van der Linden (2011a). Personality and Individual Differences, 50, 512–516. de Vries, R. E. (2011b). No evidence for a General Factor of Personality in the HEXACO Personality Inventory. Journal of Research in Personality, 45, 229–235. Figueredo, A. J., Vasquez, G., Brumbach, B. H., Sefcek, J. A., Kirsner, B. R., & Jacobs, W. J. (2005). The K-factor: Individual differences in life history strategy. Personality and Individual Differences, 39, 1349–1360. Jensen-Campbell, L. A., & Malcolm, K. T. (2007). The importance of Conscientiousness in adolescent interpersonal relationships. Personality and Social Psychology Bulletin, 33, 368–383. Krijnen, W. P. (2004). Positive loadings and factor correlations from positive covariance matrices. Psychometrika, 69, 655–660. Loehlin, J. C., & Martin, N. G. (2011). The general factor of personality: Questions and elaborations. Journal of Research in Personality, 45, 44–49. Musek, J. (2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233. Pace, V. L., & Brannick, M. T. (2010). How similar are personality scales of the same construct? A meta-analytic investigation. Personality and Individual Differences, 49, 669–676. Petrides, K. V., Vernon, P. A., Schermer, J. A., Ligthart, J., Boomsma, D. I., & Veselka, L. (2010). Relationships between trait emotional intelligence and the Big Five in the Netherlands. Personality and Individual Differences, 48, 906–910. Rushton, J. P., & Irwing, P. (2011). The General Factor of Personality: Normal and abnormal. In: T. Chamorro-Premuzic, S. von Strumm, & A. Furnham (Eds.), The Wiley-Blackwell handbook of individual differences. Blackwell Publishing. Rushton, J. P., Bons, T. A., Ando, J., Hur, Y.-M., Irwing, P., Vernon, P. A., et al. (2009). A General Factor of Personality from multitrait-multimethod data and crossnational twins. Twin Research and Human Genetics, 12, 356–365. van der Linden, D., te Nijenhuis, J., Cremer, M., & van der Ven, C. (2011). General Factors of Personality in six datasets and a criterion-related validity study at the Netherlands armed forces. International Journal of Selection and Assessment, 19, 157–169. van der Linden, D., Scholte, R. H. J., Cillessen, A. N. H., te Nijenhuis & Segers, E. (2010). Classroom ratings of likeability and popularity are related to the Big Five and the General Factor of Personality. Journal of Research in Personality, 44, 669–672. van der Linden, D., te Nijenhuis, J., & Bakker, A. B. (2010). The General Factor of Personality: A meta-analysis and a criterion-related validity study. Journal of Research in Personality, 44, 315–327. Vermulst, A. A., & Gerris, J. R. M. (2005). Quick Big Five personality test manual. The Netherlands, LCD: Leeuwarden.
Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
The General Factor of Personality and peer-rated social status: A rejoinder to de Vries (2011) Dimitri van der Linden ⇑ Institute of Psychology, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands
a r t i c l e
i n f o
Article history: Received 25 January 2011 Received in revised form 5 July 2011 Accepted 10 July 2011 Available online 6 August 2011 Keywords: Big Five General Factor of Personality Social status
a b s t r a c t In a previous study we showed that self-reported Big Five scores and the General Factor of Personality (GFP) were related to peer-ratings of likeability and popularity (van der Linden, Scholte, et al., 2010). de Vries (2011a) re-analyzed our data and concluded that (i) there was no evidence of a GFP, and (ii) the GFP we used was latent factor of Extraversion. In this rejoinder I present arguments that compromise the re-analysis and conclusions as described by de Vries (2011a) and emphasize the relevance of the GFP. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Recently, Personality and Individual Differences published an article of de Vries (2011a) who discussed our study on personality and social status (van der Linden, Scholte, Cillessen, te Nijenhuis, & Segers, 2010). de Vries re-analyzed the data as described in our article and questioned our conclusions about the General Factor of Personality (GFP). In the present paper, I will reply to the findings of de Vries (2011a) and present arguments to support the conclusions that we described in our 2010 paper. In order to provide a context for this reply, I will first give a short overview of the van der Linden, Scholte, et al. (2010) study and of the re-analysis as described in de Vries (2011a). In the van der Linden, Scholte, et al. (2010) study, 512 high school classmates (Mage = 14.8 years) from 22 different classes could freely nominate classmates on a range of social status questions. This sociometric approach provided information about the likeability and popularity of the participants. We also had access to students’ self-reports of personality as assessed with the Quick Big Five (QBF) questionnaire (Vermulst & Gerris, 2005). The van der Linden et al. article contained two main messages. The first was that self-reported Big Five factors were related to peer-ratings. Particularly Extraversion and Emotional Stability were positively related to likeability and popularity. Agreeableness was positively related to likeability and Conscientiousness was negatively related to popularity. These findings are relevant because currently only few studies have examined the relationship between self-reported personality and sociometric measures of social status. ⇑ Tel.: +31 10 408 2454; fax: +31 10 408 9009. E-mail address: [email protected] 0191-8869/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2011.07.010
The second message in the van der Linden, Scholte, et al. (2010) article was that likeability and popularity were related to the GFP. The GFP is a topic that is receiving increasing attention in the literature and several researchers assume that this general factor occupies the apex of the hierarchical structure of personality (e.g., Musek, 2007; Rushton & Irwing, 2011). The evidence that a GFP exists in many personality measures is indisputable (Rushton & Irwing, 2011; van der Linden, te Nijenhuis, & Bakker, 2010). Nevertheless, there is an ongoing debate about the nature of this construct. Several researchers have suggested that the GFP may be a substantive factor with theoretical implications (Figueredo et al., 2005; Rushton & Irwing, 2011). However, others have suggested that the GFP may not be much more than a statistical and methodological artifact (e.g., Anusic, Schimmack, Pinkus, & Lockwood, 2009). In previous studies, the GFP has been operationalized as the first unrotated factor in personality measures or as a latent factor using Confirmatory Factor Analysis (CFA) or Structural Equation Modeling (SEM). In the van der Linden, Scholte, et al. (2010) study we used both methods to show that the GFP was positively related to likeability as well as popularity. We argued that this finding has implications for the substantive versus artifact debate because if the GFP would only be a measurement artifact it is not clear why it would relate to peer-ratings of social status. So, in our study we suggested that the GFP may indeed reflect a substantive personality factor that affects how classmates perceive each other. From his recent article, it can be inferred that de Vries (2011a) agrees with our findings on the associations between the Big Five and social status; his critique mainly focuses on our findings regarding the GFP. More specifically, de Vries re-analyzed our study correlation matrix and concluded that the data does not provide evidence for a GFP. This conclusion was mainly based on two
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findings. First, de Vries constructed an alternative CFA/SEM model without an explicit GFP, but with an equal number of degrees of freedom that showed a better fit than our original GFP model. Second, in regression analyses, the GFP did not predict social status beyond Extraversion (for details see de Vries, 2011a). In the present reply, I describe several limitations in the argumentation and re-analyses of de Vries (2011a) re-emphasize the relevance of our previous findings for GFP research. 2. The GFP model versus alternative models In his paper, de Vries constructed an alternative CFA/SEM model (see Figure 2, de Vries, 2011a, p. 514) without a GFP and in which only Extraversion positively related to likeability (.37) and popularity (.32). Based on several fit indices de Vries concluded that although the original GFP model had an acceptable fit, the alternative model has a better fit. I do not question this finding. Yet, to understand the limitations of this alternative model it is important to note that the major criteria to establish good CFA/SEM models are (i) to provide the best possible reproduction of the sample correlation matrix, which can be relatively easy, for example by including many correlated errors, but also (ii) to provide a solution that is in accordance with a thorough theoretical account of the model (Barrett, 2007). This latter criterion is more difficult to fulfill than the former. In my view, an important limitation of de Vries’ (2011a) model is that the second criterion of the CFA/SEM approach was not met. Specifically, de Vries included several correlated errors between the Big Five factors without providing an explanation for them. So, he simply eliminated the paths between the Big Five factors and the GFP in the original model and re-modeled these substantive paths as correlated errors. In addition, he added two new correlated errors. Obviously, the model fit might increase in that way because the sample correlation matrix will be better represented. Nevertheless, this model also leads to additional conceptual problems. For example, taking away the GFP from a model but still allowing for relevant correlations between the lower-order personality factors can be considered a superficial method that relieves the researcher from providing theoretical explanations about why the factors are correlated in the first place. For example, de Vries based his choice for correlated errors on validation data of the Quick Big Five (Vermulst & Gerris, 2005) questionnaire (N = 19,907). In that data, Extraversion was still substantially related to Openness (.41), Agreeableness (.23), and Emotional Stability (.14). Agreeableness was related to Openness (.44) and Conscientiousness (.33). Thus, one major problem with the de Vries’ alternative model is that it still allows for correlations between factors that are theoretically unaccounted for. In contrast, models that contain a GFP provide at least an explanation for such correlations, namely that they are caused by an underlying mechanism that pushes lower-order traits towards the socially desirable end of the scale. Currently, the search on what this mechanism might be is ongoing. I will not elaborate on this in the present reply but I wish to mention that a good candidate for explaining this mechanism that has been described in the literature is emotional intelligence (Petrides et al., 2010). A final remark in this context is that in the debate about the GFP, different statistical models should be based on the different theoretical accounts that exist in this area. This would imply that in the GFP debate the alternative models to be tested against each other should contain higher-order factors (from factor intercorrelations) versus models that assume independent factors. 3. Is it only Extraversion? The other major argument in the de Vries article is that the GFP as described in van der Linden, Scholte, et al. (2010) represents
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nothing more than a latent Extraversion factor. This argument was based on the fact that the loading of Extraversion on the GFP was relatively strong, namely .79 in the factor analysis (Principal Factoring) and .84 in the CFA/SEM model. The loadings of the other factors were lower (.45, .40, and .30, for ES, A, and O, respectively) and Conscientiousness did not load on the GFP. There is no doubt that the GFP-factor loadings in this specific study partly compromised the sample-based GFP as a well-balanced mix of traits. Nevertheless, there are arguments that support that the GFP variable in van der Linden et al. is a relatively good marker of the GFP as described in previous studies. For example, in addition to constructing a GFP based on sample loadings van der Linden, Scholte, et al. (2010) also constructed a GFP based on meta-analytic loadings, using the 212 studies and 144,117 participants as reported in van der Linden, te Nijenhuis, et al. (2010). These meta-analytic loadings were .42, .63, .57, .57, and .62, for O, C, E, A, and ES, respectively. A GFP based on these loadings can truly be considered a balanced mix of all Big Five factors. The meta-analytic based GFP correlated no less than .86 with the sample-based GFP (van der Linden, Scholte, et al., 2010, p. 670). If the GFP would only represent a latent Extraversion factor it is unclear why it is so highly correlated with a variable that is made up of all the Big Five factors. In his article, de Vries does not refer to this important finding. Another argument against the notion of the GFP as a pure latent Extraversion factor is that even in the re-analysis of de Vries, Extraversion still shared a significant proportion of its variance with other Big Five factors: In the van der Linden et al. sample it mainly overlapped with Emotional Stability (r = .42), Agreeableness (r = .31), and Openness (r = .17). The latter two factors were also related to several other Big Five factors. The only trait that showed a deviating value in that sample was Conscientiousness with a correlation of r = .07 with Extraversion. So, even though Extraversion showed the strongest loading on the GFP, the Extraversion score itself consisted of a mix of different measures. The fact that Extraversion was not independent from other traits was acknowledged in the alternative CFA/SEM model of de Vries because he allowed this construct to correlate with three of the four remaining Big Five factors. de Vries also conducted separate regression analyses with likeability and popularity as dependent variables in which he entered Extraversion in the first step and the GFP in the second step. These analyses showed that Extraversion explained the largest part of the variance and adding the GFP in the second step led to only small increases in explained variance. In my view, these analyses mainly confirmed what we already knew before, namely that in our sample Extraversion had a strong GFP loading. Nevertheless, I wish to emphasize again that Extraversion itself was partly a mix of different Big Five measures. This finding can be compared to findings from the general cognitive ability factor g. In testing whether g can predict an outcome measure, say job performance, one can also use regression analyses. However, when g is entered in a regression after one has entered the score of the subtest with the highest gloading (for example a score on a reasoning subtest), then the contribution of g might be modest or even disappear. The reason for this is that g is strongly present in the specific subtest in the battery. So, in fact one tests for the effect of g after controlling for g. In line with the idea of a general factor, the appropriate analysis would be to test the extent to which the unique variance of the Big Five contributes to predicting relevant outcome variables after controlling for the GFP. This analysis is reported in the van der Linden, Scholte, et al. (2010) study. An alternative would be to test whether the GFP contributes to predicting the outcome variables (i.e., likeability, popularity) after controlling for the unique variance of the Big Five. The results of such a test would be nearly identical to the regression analysis as described in van der Linden, Scholte, et al. (2010). Specifically, I conducted the analyses with likeability
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and popularity as dependent variables and with the unique variance of the Big Five in the first step of a regression analysis and the GFP in step 2. In these analyses, the total unique variance of the Big Five explained a significant 4% of the variance in likeability and 9% in popularity. The GFP in step 2 contributed a significant 10% of the variance in likeability and 8% of popularity. In sum, it is apparent that in the van der Linden et al. study Extraversion showed the strongest association with social status. This is consistent with previous studies on personality and popularity (e.g., Anderson, John, Keltner, & Kring, 2001). However, GFP theory assumes that individual personality traits consist of unique variance plus a proportion of variance that is shared with other personality traits. The van der Linden, Scholte, et al. (2010) study indicated that the unique variance of several Big Five factors as well as their proportion of variance shared with other traits, i.e. the GFP, were related to social status.
4. The low Conscientiousness loading de Vries (2011a) mentioned that in the van der Linden, Scholte, et al. (2010) study, the specific loading of Conscientiousness on the GFP was low, which is in contrast with the findings of a large metaanalysis that found a mean Conscientiousness-GFP loading of .63 (van der Linden, te Nijenhuis, et al., 2010). Thus, a relevant question is how to interpret the low loading of Conscientiousness in the van der Linden, Scholte, et al. (2010) study. One way to address this question is in terms of measurement or sampling variability. For example, some studies have found that Conscientiousness was significantly related to social status in adolescents (e.g., Jensen-Campbell & Malcolm, 2007), whereas other studies found it was not (e.g., Anderson et al., 2001). A possible explanation for such discrepancies is that different measures of the Big Five may focus on different aspects of the traits. Conscientiousness, for instance, consists of aspects such as showing integrity, being reliable, working hard, and working carefully. From GFP theory it can be inferred that not all aspects of Conscientiousness have to be strongly related to the general factor. It can be expected that the magnitude of the GFP loadings of specific personality measures depends on the extent to which they contain aspects of social desirability (see also: Bäckström, Björklund, & Larsson, 2009). This idea fits with the hypothesis that the GFP is a mechanism that has a unidirectional influence on many personality traits, namely towards higher social desirability (Rushton & Irwing, 2011). Regarding this, it is important to note that in the Quick Big Five measure as used in van der Linden, Scholte, et al. (2010), particularly the ‘working carefully’ aspect of Conscientiousness was measured. This becomes apparent in the six Conscientiousness items, which are ‘careful’, ‘orderly’, ‘neat’, ‘accurate’, ‘systematic’, and ‘disorganized’ (reversely coded). Although further research is necessary, it is plausible that for adolescents these aspects of personality are not necessarily socially desirable in the sense that they are helpful in order to gain friends, a partner, or social recognition. As such, it would not be unusual that the GFP-loading of this scale is low. Beyond looking at the different aspects of Conscientiousness, there may be more general reasons to suggest that it may not be very relevant to focus on the low GFP-loading of one specific trait in one sample. More specifically, recently Pace and Brannick (2010) and Barrett and Rolland (2009) argued that in the various instruments and samples there is large variability in the characteristics of the Big Five. Barrett and Rolland (2009) looked at the correlations between Conscientiousness and Emotional Stability in nine published meta-analyses and found that these correlations ranged from .17 to .70. They argued that such findings require serious attention to the stability of personality measures. I agree with
Barrett and Rolland (2009) and with Pace and Brannick (2010) that the Big Five characteristics, including their intercorrelations, show strong variability. In our own meta-analysis on the Big Five intercorrelations (van der Linden, te Nijenhuis, et al., 2010) we also found wide ranges of intercorrelations between traits. For example, between the individual studies in the meta-analysis, the correlation between Conscientiousness and Extraversion ranged from from .20 (based on a N = 2901) to .61 (based on a N = 1054). Other Big Five intercorrelations showed similar levels of variability. Levels of variability as reported above are not what one would expect if one considers the Big Five as relatively clearly defined and stable constructs. Yet, such large variability exists and can be found in published and peer-reviewed articles that have mainly used well-known and validated instruments. The point of this is that large variability in personality measurement may need attention, but in any case would be a general issue in personality research and not specifically related to the GFP. Consequently, for the broader theory of the GFP it may not be very useful to give much attention to an occasional low loading of a specific trait. Regarding this, a relevant observation is that despite the variability in Big Five intercorrelations, the higher-order factors that emerge from them may be quite stable. For example, in a recent study (N 21.000) we showed that the GFPs derived from six different personality measures substantially overlapped, with a mean correlation of r = .53 and a range from .40 to .67 (van der Linden, te Nijenhuis, Cremer, & van der Ven, 2011). Some of these measures were based on the Big Five model (e.g., the NEO-PI-R) and others were not (e.g., Guilford Temperament Survey). In addition, Rushton et al. (2009) reported a correlation of .72 between the GFPs from the Tridimensional Personality Questionnaire (TPQ) and the NEO. Loehlin and Martin (2011) reported correlations ranging from .75 to .80 between measures based on Cloninger’s personality model (TPQ) and Eysenck’s model (EPQ). Finally, Rushton and Irwing (2011) reported Confirmatory Factor Analyses results from four personality questionnaires showing that the GFPs from these measures are nearly identical. Compared to this rather consistent set of findings from different studies, the only study that reported deviant results and did not find a strong relationship between GFPs from different measures was the one of de Vries (2011b) who used questionnaires based on the Big Five and the HEXACO model.
5. GFP research: some general issues The questions that de Vries raised about the GFP specifically relate to the study of van der Linden, Scholte, et al. (2010), but from the arguments I provided above it may be clear that they also relate to more general points in GFP research, namely about consistency and sample fluctuations of the construct. Although de Vries questioned the presence of the GFP in our study, it cannot be denied that in the majority of Big Five or other personality measures there is a common factor that reflects social desirability. In fact, this factor has been known for decades and has also been shown in numerous more recent studies (Loehlin & Martin, 2011; Musek, 2007; Rushton & Irwing, 2011; van der Linden, te Nijenhuis, et al., 2010). Consequently, the GFP debate does not focus on whether such a factor exists but on its interpretation. Proponents of the GFP suggest that it reflects social desirability in a true sense, implying that it may have relevance for many life areas such as job performance, social behavior, and psychological and somatic health (Figueredo et al., 2005). Several studies that looked at the genetics of personality traits suggest that the GFP has a relevant genetic component, which provides additional support for the substantive account of the general factor (e.g., Loehlin & Martin, 2011; Rushton et al., 2009). The majority of the GFP opponents would agree that the construct reflects social
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desirability, but more in terms of response bias or measurement artifact (Anusic et al., 2009; de Vries, 2011b). Although this social desirability factor that is referred to as the GFP is relatively consistent over samples and measures, there is nevertheless sample fluctuation. For example, in a minority of samples one or more lower-level personality traits sometimes show relatively modest to low loadings on the GFP. Also, individual personality scales may sometimes show different loadings on different GFPs. For example, in the study of Loehlin and Martin (2011) the GFP in an adult sample displayed different factor loadings than the GFP from an adolescent sample, even though the same questionnaire was used in both samples (The EPQ). It currently remains an open question whether such variability is due to random sampling error, reflects systematic differences between samples, or is due to other reasons. Yet, it is unrealistic to expect that in each and every sample, the GFP is perfectly represented. Consequently, it is also unrealistic to require that in every individual sample the GFP will fulfill the strictest of criteria to show its existence (e.g., optimal model fit, maximum likelihood). This would be just as harsh as requiring that in each and every individual sample that uses the Big Five (or any other personality model) there is an empirical confirmation of that model. For example, that in every study items should load on the designated dimensions and that intercorrelations between the Big Five are identical from one study to the other. It is obvious that such confirmation will not be found in many studies, but that does not compromise the relevance of the Big Five. In the light of this, it is clear that the GFP in the van der Linden, Scholte, et al. (2010) study had some limitations. This was acknowledged by the authors (p. 672). Nevertheless, in the arguments described above I argue that the factor that was extracted was more than a latent factor of one single Big Five dimension but reflected the shared variance. This shared variance points into the direction of a more general social desirable tendency involving sociability, kindness, and a propensity to experience a stable and positive mood. The GFP that was extracted from the sample loadings showed a strong overlap (r = .86) with a GFP that was based on stable, meta-analytic loadings. Such a finding would not be expected if the GFP in the van der Linden, Scholte, et al. (2010) study would merely reflect a single Big Five factor. Instead the overlap between GFPs supports the idea of a general factor. Finally, the sample-based as well as the meta-analytically based GFPs showed associations with peer ratings of likeability and popularity. As a final remark, it is important to note that in the social sciences no single study can confirm or disconfirm a specific theory. This may be even more so in an area such as personality research where the various measures of presumed identical constructs sometimes show considerable variability. A good approach would be to increase knowledge by discovering general trends over a large number of different studies, each with their limitations. Some individual studies will make a strong case in favor of or against a specific theory; other will make a more modest contribution. Further, it is important to acknowledge that factor analytic techniques have several limitations. For example, Krijnen (2004) argued that any matrix with positive elements allows the extraction of a general factor. That statistical phenomenon in itself does not necessar-
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ily provide useful information about the nature or the consistency of such a factor. In addition, factor analytic techniques are not sufficient to establish causal relationships. In order to test whether the GFP indeed reflects an underlying construct affecting personality traits, it would be useful to collect data that may reveal causal effects of the GFP on lower-order traits as well as of the GFP on other relevant outcome variables such as health and social functioning. Longitudinal or experimental studies may be a way to collect such data. Thus, different types of studies are required to form a coherent picture on the viability and theoretical relevance of the GFP. References Anderson, C., John, O. P., Keltner, D., & Kring, A. M. (2001). Who attains social status? Effects of personality and attractiveness in social groups. Journal of Personality and Social Psychology, 81, 116–132. Anusic, I., Schimmack, U., Pinkus, R. T., & Lockwood, P. (2009). The nature and structure of correlations among Big Five ratings: The Halo-Alpha-Beta model. Journal of Personality and Social Psychology, 97, 1142–1156. Bäckström, M., Björklund, F., & Larsson, M. R. (2009). Five-factor inventories have a major general factor related to social desirability which can be reduced by framing items neutrally. Journal of Research in Personality, 43, 335–344. Barrett, P. (2007). Structural equation modeling: Adjudging model fit. Personality and Individual Differences, 42, 815–824. Barrett, P., & Rolland, J. P. (2009). The meta-analytic correlation between two Big Five factors: Something is not quite right in the woodshed. The Strategic White paper Series. http://pbarrett.net/stratpapers/metacorr.pdf. de Vries, R. E. (2011a). No support for a general factor of personality in a reanalysis of Van der Linden (2011a). Personality and Individual Differences, 50, 512–516. de Vries, R. E. (2011b). No evidence for a General Factor of Personality in the HEXACO Personality Inventory. Journal of Research in Personality, 45, 229–235. Figueredo, A. J., Vasquez, G., Brumbach, B. H., Sefcek, J. A., Kirsner, B. R., & Jacobs, W. J. (2005). The K-factor: Individual differences in life history strategy. Personality and Individual Differences, 39, 1349–1360. Jensen-Campbell, L. A., & Malcolm, K. T. (2007). The importance of Conscientiousness in adolescent interpersonal relationships. Personality and Social Psychology Bulletin, 33, 368–383. Krijnen, W. P. (2004). Positive loadings and factor correlations from positive covariance matrices. Psychometrika, 69, 655–660. Loehlin, J. C., & Martin, N. G. (2011). The general factor of personality: Questions and elaborations. Journal of Research in Personality, 45, 44–49. Musek, J. (2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233. Pace, V. L., & Brannick, M. T. (2010). How similar are personality scales of the same construct? A meta-analytic investigation. Personality and Individual Differences, 49, 669–676. Petrides, K. V., Vernon, P. A., Schermer, J. A., Ligthart, J., Boomsma, D. I., & Veselka, L. (2010). Relationships between trait emotional intelligence and the Big Five in the Netherlands. Personality and Individual Differences, 48, 906–910. Rushton, J. P., & Irwing, P. (2011). The General Factor of Personality: Normal and abnormal. In: T. Chamorro-Premuzic, S. von Strumm, & A. Furnham (Eds.), The Wiley-Blackwell handbook of individual differences. Blackwell Publishing. Rushton, J. P., Bons, T. A., Ando, J., Hur, Y.-M., Irwing, P., Vernon, P. A., et al. (2009). A General Factor of Personality from multitrait-multimethod data and crossnational twins. Twin Research and Human Genetics, 12, 356–365. van der Linden, D., te Nijenhuis, J., Cremer, M., & van der Ven, C. (2011). General Factors of Personality in six datasets and a criterion-related validity study at the Netherlands armed forces. International Journal of Selection and Assessment, 19, 157–169. van der Linden, D., Scholte, R. H. J., Cillessen, A. N. H., te Nijenhuis & Segers, E. (2010). Classroom ratings of likeability and popularity are related to the Big Five and the General Factor of Personality. Journal of Research in Personality, 44, 669–672. van der Linden, D., te Nijenhuis, J., & Bakker, A. B. (2010). The General Factor of Personality: A meta-analysis and a criterion-related validity study. Journal of Research in Personality, 44, 315–327. Vermulst, A. A., & Gerris, J. R. M. (2005). Quick Big Five personality test manual. The Netherlands, LCD: Leeuwarden.