A Latent State-Trait Analysis of Implicit and Explicit Personality Measures. Stefan C. Schmukle and Boris Egloff

Transcription

1 IMPLICIT AND EXPLICIT MEASURES 1 Running Head: IMPLICIT AND EXPLICIT MEASURES A Latent State-Trait Analysis of Implicit and Explicit Personality Measures Stefan C. Schmukle and Boris Egloff Johannes Gutenberg-University Mainz, Germany European Journal of Psychological Assessment This manuscript was published in: Schmukle, S. C. & Egloff, B. (2005). A latent state-trait analysis of implicit and explicit personality measures. European Journal of Psychological Assessment, 21, This is an unedited version of the manuscript before copyediting, typesetting, and review of the resulting proof. Address correspondence to Stefan C. Schmukle, Department of Psychology, University of Leipzig; schmukle@uni-leipzig.de

2 IMPLICIT AND EXPLICIT MEASURES 2 Abstract Explicit personality measures assess introspectively accessible self-descriptions. In contrast, implicit personality measures assess introspectively inaccessible processes that operate outside awareness. However, similar for both kinds of trait measures, the effect of the situation in which the assessment takes place should be as small as possible. The present study aims at quantifying possible systematic occasion-specific effects on implicit measures (Implicit Association Test) and explicit measures (self-report ratings) of extraversion and anxiety by means of a latent state-trait analysis. This analysis revealed that as desired for personality assessment all four measures capture mostly stable interindividual differences. Nevertheless, occasion-specific effects were also observed. These effects were (1) more pronounced for implicit than for explicit measures and (2) more pronounced for anxiety than for extraversion. Implications for the implicit assessment of personality traits are discussed. Key words: latent state-trait analysis, IAT, implicit measurement, personality, situations

3 IMPLICIT AND EXPLICIT MEASURES 3 A Latent State-Trait Analysis of Implicit and Explicit Personality Measures In personality questionnaires, participants are explicitly asked to judge the extent to which various statements generally characterize them. Based on these responses, participants scores on different personality traits are inferred. However, because no assessment takes place in a situational vacuum, biases in personality measures due to situational effects can occur (Deinzer et al., 1995). Latent State-Trait Analysis Latent state-trait (LST) analysis helps to estimate this situational impact on trait measures. By means of this analysis, the observed variance of a test can be separated into trait-specific and systematic occasion-specific components by testing participants at different occasions of measurement (for an introduction to LST analysis, see Steyer, Schmitt, & Eid, 1999). LST analysis has already been successfully applied in different areas of psychology (e.g., Egloff, Schmukle, Burns, Kohlmann, & Hock, 2003; Eid & Diener, 1999; Schmukle, Egloff, & Burns, 2002). For a trait measure, the trait-specific component should be high and best equal the reliability. In contrast, the occasion-specific component should best be zero, thus indicating no occasion-specific effects on the measurement at all. LST analyses in the area of personality research showed that there are small, but significant occasion-specific effects in trait assessment. For different personality inventories, the proportion of occasion-specific to total variance was up to 22%, with a medium of 7% (Deinzer et al., 1995). Concerning the measurement of trait anxiety, similar results emerged (Steyer, Majcen, Schwenkmezger, & Buchner, 1989). One way to reduce these occasion-specific effects on trait estimates is to base such an estimate on different occasions, i.e., to aggregate the data across occasions (Deinzer et al., 1995).

4 IMPLICIT AND EXPLICIT MEASURES 4 Implicit Measurement In addition to occasion-specific effects, there are two further limitations of self-report personality measures that might diminish their validity (cf. Greenwald et al., 2002). The first limitation is that self-reports depend on participants willingness to report on oneself. Factors such as demand characteristics, self presentation concerns, and faking might mask the selfreport. The second limitation of self-reports is that because of lacking awareness participants might be unable to accurately indicate their true scores. This limitation refers to the impressive amount of evidence showing that individuals process information about themselves and their environment not only in an explicit (i.e., controlled or conscious) mode but also in an implicit (i.e., automatic or nonconscious) mode (Epstein, 1994; Greenwald et al., 2002; Wilson, Lindsley, & Schooler, 2000). Thus, the respondent is not able to report on these implicit cognitions because they operate outside awareness. Recently, a promising new measurement tool for assessing implicit processes was introduced: the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998). The IAT measures strengths of associations between concepts by comparing response times in two combined discrimination tasks. Participants are required to sort stimuli representing four concepts using just two responses, each assigned to two of the four concepts. Basic assumption of the IAT is that, if two concepts are highly associated, the sorting task will be easier (i.e. faster) when the two associated concepts share the same response key than when they share different response keys. In contrast to other implicit measures (Bosson, Swann, & Pennebaker, 2000), the IAT routinely shows good reliability, which is a prerequisite for measuring individual differences. We adapted the IAT to provide an implicit measure of the self-concept of anxiety (Egloff & Schmukle, 2002). For this aim, the categorization into self and other categories was combined with the classification of items into anxiety and calmness categories. An IAT effect

5 IMPLICIT AND EXPLICIT MEASURES 5 indicating implicit anxiety was computed as the difference between self + anxiety and self + calmness. Thus, by measuring the relative ease of categorizing self items with anxiety items as compared to self items with calmness items, the IAT-Anxiety effect is an indicator of the implicit self-concept of anxiety. The IAT-Anxiety exhibited good predictive validity, even when self-reported anxiety and social desirability were controlled for (Egloff & Schmukle, 2002): The IAT-Anxiety score was related to changes in experimenter-rated anxiety and performance decrements after failure. Furthermore, several behavioral indicators of anxiety during a stressful speech were predicted by the IAT-Anxiety. Additionally, the IAT-Anxiety was in contrast to an explicit anxiety measure unaffected by a faking instruction. The IAT can easily be adapted for assessing the self-concepts of other personality traits by selecting adequate categories and stimuli. For example, the IAT was applied to measure the implicit self-concept of shyness by using the categories shy and nonshy (Asendorpf, Banse, & Mücke, 2002). Similarly, the implicit self-concept of extraversion was assessed by using the categories extraversion and introversion (Mierke & Klauer, 2003). Goals of this Research The present research analyzes the extent of occasion-specific effects on IATs for assessing implicit self-concepts of personality traits. In order to compare results obtained for different traits, we assess both anxiety and extraversion. By using LST analysis, we aim at disentangling and quantifying portions of trait-specific and occasion-specific variance in these IAT scores. To contrast the results with those for explicit measures, we additionally assess extraversion and anxiety by self-report. We used the stimuli of the IATs as questionnaire items to ensure that identical material is used for implicit and explicit assessment. Thus, differences in the LST analyses for explicit and implicit measures can be traced back only to the different assessment procedures, and not to different item content.

6 IMPLICIT AND EXPLICIT MEASURES 6 Furthermore, we examine the relation between explicit and implicit personality measures for assessing both extraversion and anxiety. In general, the implicit explicit correlation seems to be quite heterogeneous for different constructs (Nosek & Banaji, 2002). Whereas there seems to be no or only a very low positive correlation for anxiety (Egloff & Schmukle, 2002), the correlation for extraversion is more substantial (Mierke & Klauer, 2003). Method Participants Seventy students of Johannes Gutenberg-University Mainz participated in this study in exchange for research participation credit. Five participants, who attended only the first session, were excluded from the analysis. The average age of the remaining 65 participants (55 women, 10 men) was 22.9 years (SD = 3.6). Procedure The procedure consisted of two sessions, with a time lag of one week. At each measurement occasion, participants first performed the implicit measures, and then the explicit measures. We believe that presenting the implicit measure first has the advantage of smaller (if any) carry-over effects from one measure to the other because implicit measures are less subject to conscious engagement. The sequence of the two implicit measures, the IAT-Extraversion and the IAT-Anxiety, was counterbalanced. Implicit Measures The IATs were administered on personal computers with the program Inquisit (Draine, 2001) by presenting stimuli from the self (me, my, own, I, self) and other (they, your, them, you, others) categories. Additionally, in the IAT-Extraversion we used stimuli from the categories extraversion (sociable, talkative, active, impulsive, outgoing) and introversion (shy, taciturn, passive, deliberate, reserved), whereas in the IAT-Anxiety items from the

7 IMPLICIT AND EXPLICIT MEASURES 7 categories anxiety (nervous, afraid, fearful, anxious, uncertain) and calmness (relaxed, balanced, at ease, calm, restful) were administered. Each IAT procedure comprises five blocks (see Table 1). Participants practiced the discrimination of self and other items (target discrimination) in the first block that comprised 20 trials (each item was presented twice). The same was done for the attribute discrimination by sorting items into extraversion and introversion categories (or anxiety and calmness categories, respectively) in Block 2 and for practicing the switched key assignment in Block 4 (20 items each). The critical Blocks 3 and 5 consisted of 20 practice trials and 60 critical trials. In these trials, participants categorized items into two combined categories, each including the attribute and the target concept that were assigned to the same key. Participants were told they would be making a series of category judgments. On each trial, a stimulus word was displayed in the center of a computer screen. Category labels were displayed on the left and right sides of the window. Participants used the letter "A" on the left side of the keyboard and the number "5 of the right-side numeric keypad for their responses. They were told, "Please try to be as accurate as possible, while also going as quick as possible. If your selection is incorrect, you will see a red "X". To continue to the next judgment, you must make the correct selection." Participants were told to keep their index fingers on the "A" and "5" keys throughout the experiment to facilitate fast responding. An intertrial interval of 150 ms was used. The computer recorded elapsed time between the start of each stimulus presentation and the correct response. Mean latencies and error rates were displayed after each block. IAT data were treated using an improved scoring algorithm (so-called D 1 measure) described by Greenwald, Nosek, and Banaji (2003): (a) trials with latencies greater than 10,000 ms were eliminated; (b) error trials were included in the analysis by using the latency until the correct response was given (built-in error penalty); (c) the mean latency in the critical

8 IMPLICIT AND EXPLICIT MEASURES 8 trials of Block 5 (self + anxiety or self + extraversion) was subtracted from the critical trials of Block 3 (self + calmness or self + introversion) separately for test and practice trials; (d) these differences were divided by the individual-respondent standard deviations of reaction times in test or practice trials, respectively; (e) the IAT effect for anxiety was computed as the average of these two scores (weighted for the number of test and practice trials). Thus, the higher the IAT effect is, the more extraverted (or anxious, respectively) is the estimated implicit self concept of a participant. Explicit Measures The participants explicitly rated the 20 attribute stimuli of the IAT (i.e., Please indicate on a scale from 0 [not at all] to 5 [very high] the extent to which the following attributes apply to you ). The 20 items were presented in random order. The score of explicit extraversion was computed as the mean of the five extraversion and the five reverse scored introversion ratings, and that of explicit anxiety as the mean of the five anxiety and the five reverse scored calmness ratings. Data analysis Figure 1 shows the latent state-trait model that allows separating a trait-specific component, an occasion-specific component, and a component due to measurement error. For this model, the observed test score had to be split into two test halves, each based on half of the reaction times or half of the items, respectively. These test halves are the manifest variables in the model, denoted by Y ik, where i represents the test half and k represents the measurement occasion. The latent trait variable T, which is measured by all of the four manifest variables, assesses stable interindividual differences. This variable characterizes a person across different occasions of measurement. In contrast, the latent occasion-specific variables O 1 and O 2, which are measured by the test halves at one specific occasion (e.g., Y 11

9 IMPLICIT AND EXPLICIT MEASURES 9 and Y 21 for the first occasion), assess systematic occasion-specific deviations from the trait variable, thus, occasion-specific interindividual differences. In this model, the degree to which interindividual differences in the test scores are stable or occasion-specific can be analyzed by comparing two variance components: consistency and occasion specificity. The consistency Con = Var( T ) Var( ) Y ik is the proportion of variance that is due to stable interindividual differences, i.e., the traitspecific component. The occasion specificity OccSpe = Var( O Var( Y k ik ) ) is the degree of variance that is due to occasion-specific interindividual differences. If the two test halves are not perfectly homogenous, test-half-specific stable interindividual differences occur, which are not considered by the model presented in Figure 1. In this case, the model shown in Figure 2 is more appropriate, because it additionally incorporates latent method-specific variables M 1 and M 2, which measure test-half-specific stable interindividual differences. In this case, the method specificity indicates the degree of this test-half-specific variance: MetSpe = Var( M i ). Var( Y ) ik These coefficients add up to the reliability coefficient (E ik is the measurement error): Var( Eik ) Rel = 1 = Con + OccSpe + MetSpe Var( Y ) ik However, the coefficients, as defined above, refer to one test half only. To calculate them for the total score, we applied aggregation equations (see Eid & Diener, 1999; Steyer &

10 IMPLICIT AND EXPLICIT MEASURES 10 Schmitt, 1990) that may be considered generalizations of the Spearman-Brown formula for lengthened tests. Results Descriptive Statistics Table 2 displays the descriptive statistics and correlations between the test halves measured at the two sessions for the IAT-Extraversion and the IAT-Anxiety. The mean scores of the IAT-Extraversion were consistently higher than those of the IAT-Anxiety. Aggregated across test halves and occasion measurements, we observed t(64) = 6.94, p <.001 (d = 1.27). As the negative IAT-Anxiety effect indicates, most participants tended to have a non-anxious implicit self-concept, whereas the implicit self-concept of extraversion was more balanced. This result was mirrored for the explicit self-concept (see Table 3). The aggregated mean of the ten extraversion and reversed introversion items was much higher than the mean of the ten anxiety and reversed calmness items, t(64) = 11.82, p <.001 (d = 2.13). For both IATs, test halves correlated higher within measurement occasions than between occasions, indicating variability in the IAT-Anxiety effects between the two sessions. In contrast, for the explicit measures, there was no obvious systematic variation within the inter-correlations. The issue of variability and stability of the scores between measurement occasions was examined more thoroughly by applying an LST analysis that aimed at identifying occasion-specific effects on implicit and explicit personality measures. Latent State-Trait Analysis For estimating the different models, we employed Mplus Version 2.12 (Muthén & Muthén, 2001) by using maximum likelihood estimation. For the implicit measures, we applied the LST model without method-specific variances (see Figure 1). Table 4 displays the model fit statistics along with the latent variances and the coefficients of the LST analysis. For both the IAT-Extraversion and the

11 IMPLICIT AND EXPLICIT MEASURES 11 IAT-Anxiety, the LST models fit the data very well. Reliability was in the expected good range, and consistency was substantially higher than occasion specificity. To test the significance of occasion specificity, we analyzed a latent trait model without latent occasionspecific variables. This model fit the data neither for extraversion, χ 2 (8) = 23.22, p <.01, nor for anxiety, χ 2 (8) = 28.92, p <.001, showing that there are significant occasion-specific effects on both IATs. However, the analyses also showed differences between the two IATs: In comparison with the IAT-Anxiety, the IAT-Extraversion showed higher consistency and lower occasion specificity coefficients. Next, we employed similar analyses to the explicit ratings. In this case, the LST model without method factors, as we used for the implicit measures, fit the data neither for explicit extraversion, χ 2 (7) = 33.85, p <.001, nor for explicit anxiety, χ 2 (7) = 31.06, p <.001. This indicates that the two test halves are not perfectly equivalent and show some heterogeneity in their items. Consequently, we employed an LST model with latent method variables to consider test-half-specific variance (see Figure 2). This model fit the data well for both explicit extraversion and anxiety, as the correspondent fit statistics in Table 4 show. For both of the explicit measures, reliability and consistency were very high, whereas occasion and method specificity were rather low (see Table 4). This indicates that most of the reliable variance captures stable interindividual differences. Even a latent trait model fit the data for extraversion, χ 2 (7) = 10.96, p =.14, suggesting that there is no significant occasion specificity at all. In contrast, the occasion specificity of explicit anxiety differed significantly from zero, as shown by the insufficient fit of the trait model, χ 2 (7) = 25.25, p <.001. Furthermore, we conducted separately for extraversion and anxiety a LST model that simultaneously analyzed implicit and explicit measures. This model explored both the relationship between implicit and explicit trait variables and the association between implicit and explicit occasion-specific variables. This kind of analysis is structurally identical to a

12 IMPLICIT AND EXPLICIT MEASURES 12 multi-construct LST analysis (cf. Schmitt, 2000; Schmukle et al., 2002). In this simultaneous LST analysis, the LST models for implicit and explicit measures were combined to one model. In this combined model, (1) the latent trait variables of implicit and explicit measures were allowed to covary and (2) the occasion-specific latent variables of implicit and explicit measures at the same measurement occasion were allowed to covary. The covariances of the occasion-specific variables were set equal between measurement occasions. The simultaneous LST model for extraversion fit the data very well, χ 2 (27) = 32.63, p =.21. All estimated latent variances were the same as those estimated with the separate LST models (see Table 4). The latent correlation between implicit and explicit extraversion was r =.35, p =.02. In contrast, the latent correlation between occasion-specific variables of the same measurement occasion was not significant, r =.27. For anxiety, the simultaneous model also showed a very good fit, χ 2 (27) = 27.40, p =.44. As in the model for extraversion, all latent variances were identical to those obtained with the separate LST analyses (Table 4). However, in contrast to the results for extraversion, none of the latent correlations was significant: For the correlation between implicit and explicit anxiety we observed r =.03, and for the correlation between the occasion-specific variables r =.14. In sum, the LST analyses revealed that all four measures exhibited good reliability. Most of this reliable variance captured stable interindividual differences, as shown by the fact that consistency clearly exceeded occasion specificity. However, the extent of occasionspecific effects differed between the four measures: The impact of situations on the assessment as indicated by the occasion specificity was (1) higher for implicit than for explicit measures and (2) higher for anxiety than for extraversion. The occasion-specific effects did not covary between implicit and explicit measures, i.e. both measurement methods are susceptible to different causes of intraindividual change.

13 IMPLICIT AND EXPLICIT MEASURES 13 Relation Between Extraversion and Anxiety Additionally, we performed correlational analyses to analyze the relation between the two constructs extraversion and introversion. In correspondence with empirical evidence and theoretical reasoning (e.g., Eysenck & Eysenck, 1985), we found no associations between extraversion and anxiety, neither for the implicit measures, r =.08 at the first and r =.03 at the second occasion, nor for the explicit measures, r =.12 and r =.01, respectively. Discussion This study analyzed the extent of occasion-specific effects on implicit and explicit personality measures of extraversion and anxiety by means of LST analysis. We used two adaptations of the IAT for assessing extraversion and anxiety as implicit measures, and selfreport ratings of these dimensions as explicit measures. The LST analysis indicated that all four measures fulfill the psychometric properties that are necessary for personality assessment: (1) they show good reliability and (2) the reliable variance captures mostly stable interindividual differences, as is shown by high consistency and low occasion specificity coefficients. However, there was also evidence for situational effects on these measures. Regarding the self-report ratings, we found small occasion-specific and method-specific effects, confirming the results that Deinzer et al. (1995) obtained with the NEO Five-Factor Inventory (Costa & McCrae, 1992) and the Eysenck Personality Inventory (Eysenck & Eysenck, 1968). That is, explicit personality measures are influenced by situational effects to a small degree. In contrast, the IATs for assessing personality are somewhat more affected by situations than explicit measures, as indicated by higher occasion-specificity. Similar effects were observed for an IAT that assesses attitudes toward gay men (Steffens & Buchner, 2003). Furthermore, these results also correspond with the pattern of good internal consistency and only moderate stability, which is typically found for IATs independent of the construct that

14 IMPLICIT AND EXPLICIT MEASURES 14 is being measured (Banse, Seise, & Zerbes, 2001; Bosson et al., 2000; Cunningham, Preacher, & Banaji, 2001; Egloff, Schwerdtfeger, & Schmukle, 2004; Greenwald & Farnham, 2000). The fact that different IATs are all substantially affected by occasion-specific factors suggests that features of the IAT procedure itself are responsible for these effects. The low correlation between occasion-specific variables of IATs and self-reports gives further evidence for this assumption, because it indicates that IATs are affected by other occasionspecific factors than self-reports are. Changing the test taking strategy might be such a factor that is specific for the IAT, for example, when participants try something out during the second test. Likewise, learning effects could be the reason (e.g., participants are more familiar with the procedure at the second occasion). Furthermore, participants might think about the purpose and the construction of the IAT during the pause between test and retest. All these factors would lead to occasion-specific variance that is specific for IAT measures. Certainly, further research that examines these processes is warranted. Additionally, the LST analysis revealed that occasion-specific effects were higher for the construct anxiety than for the construct extraversion. This was observed for both implicit and explicit measures. Occasion-specific interindividual differences in affective states might be responsible for this effect, because it has been shown that affective states influence the judgment of well-being, happiness, and satisfaction with one's life (Schwarz & Clore, 1983). To evaluate the size of the LST coefficients found for the IAT-Anxiety (consistency of.56 and occasion specificity of.26), we compared them with those of self-report state and trait scales. For the state version of the State-Trait Anxiety Inventory (Spielberger, Gorsuch, & Lushene, 1979), consistency was about.40 and occasion specificity was about.50, whereas for the trait version, consistency was about.80 and occasion specificity was.10 at maximum (Steyer et al., 1989). Similarly, we found consistency of.75 and occasion specificity of.09 for the explicit trait anxiety measure in the present study. This comparison suggests that the IAT-

15 IMPLICIT AND EXPLICIT MEASURES 15 Anxiety is neither a pure trait nor a pure state measure but lies in-between. Thus, the IAT- Anxiety might not only be useful as a trait measure of anxiety, but also as a state measure. However, two studies in which a state of anxiety was experimentally induced by a speaking task did not provide evidence for this assumption. The IAT-Anxiety was not influenced by such an experimental manipulation (Schmukle & Egloff, 2003). Concerning the correlation between implicit and explicit measures, we obtained different results for extraversion and anxiety. For anxiety, we replicated previous studies (Egloff & Schmukle, 2002, 2003) that reported no significant correlations. In contrast, the correlation between implicit and explicit extraversion was more pronounced, confirming the results of Mierke and Klauer (2003). One reason for this difference might be that extraversion is less influenced by social desirability, leading to higher convergence between implicit and explicit measures. However, both IATs fall behind a minimum level of convergent validity a challenge to the assumption that implicit and explicit personality tests are two different ways to measure the same underlying construct, a view that mirrors Cattell s (1957) distinction of Q-data (questionnaire data) and T-data (test data). According to this distinction, personality IATs are classified as so-called objective tests of personality that are supposed to converge with personality questionnaires. Alternatively, implicit and explicit tests can be assumed not only as two ways of measurement but also as measures of two different personality constructs (e.g., implicit and explicit self-concept of extraversion). These different constructs are the consequence of two different modes of functioning, an implicit (automatic, impulsive) and an explicit (controlled, reflective) mode (Greenwald et al., 2002; McClelland, Koestner, & Weinberger, 1989; Strack & Deutsch, in press; Wilson et al., 2000). These modes might well function independently, leading to a dissociation of implicit and explicit measures. Not only the low correlation between implicit and explicit tests but also differential predictive validity

16 IMPLICIT AND EXPLICIT MEASURES 16 gives evidence for the view of two different constructs: Personality IATs predict spontaneous or automatic behavior better than controlled behavior, whereas self-report predicts controlled behavior better than spontaneous or automatic behavior (Asendorpf et al., 2002; Egloff & Schmukle, 2002). In sum, the LST analysis shows that IATs for assessing anxiety and extraversion might be used as personality measures because they show good reliability and sufficiently high consistency. The results are also promising in that they suggest that personality traits in general might be implicitly assessed via the IAT. However, there were also substantial occasion-specific effects on the IATs observed.

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21 IMPLICIT AND EXPLICIT MEASURES 21 Author Note Stefan C. Schmukle and Boris Egloff, Department of Psychology, Johannes Gutenberg-University Mainz, Germany. This research was supported by Deutsche Forschungsgemeinschaft (German Research Foundation) Grant EG 143/1-1. We thank Florian Weck for his help with data collection. We also thank Judith Kappesser for helpful comments on an earlier version of this article. Correspondence concerning this article should be addressed to Stefan C. Schmukle, Department of Psychology, Johannes Gutenberg-University Mainz, D Mainz, Germany. Electronic mail may be sent to

22 IMPLICIT AND EXPLICIT MEASURES 22 Table 1 Task Sequence of the Implicit Association Tests (IAT) IAT-Extraversion IAT-Anxiety Block No. of trials Task Left key Right key Left key Right key 1 20 Target discrimination Me Others Me Others 2 20 Attribute discrimination Introversion Extraversion Calmness Anxiety Initial combined task Me, Introversion Others, Extraversion Me, Calmness Others, Anxiety 4 20 Reversed attribute discrimination Extraversion Introversion Anxiety Calmness Reversed combined task Me, Extraversion Others, Introversion Me, Anxiety Others, Calmness

23 IMPLICIT AND EXPLICIT MEASURES 23 Table 2 Descriptive Statistics and Correlations for Test Halves of the Implicit Measures M SD IAT 11 IAT 21 IAT 12 IAT 22 Extraversion IAT IAT IAT IAT Anxiety IAT IAT IAT IAT Notes. N = 65. IAT = Implicit Association Test Effect. The first index refers to the test half, the second to the measurement occasion. For all correlations p <.001.

24 IMPLICIT AND EXPLICIT MEASURES 24 Table 3 Descriptive Statistics and Correlations for Test Halves of the Explicit Measures M SD SR 11 SR 21 SR 12 SR 22 Extraversion SR SR SR SR Anxiety SR SR SR SR Notes. N = 65. SR = Self Report (item means; range: 0 5). The first index refers to the test half, the second to the measurement occasion. For all correlations p <.001.

25 IMPLICIT AND EXPLICIT MEASURES 25 Table 4 Results of the Latent State-Trait (LST) Analyses Model Fit Latent Variances LST Coefficients a χ 2 df p Trait Occasion Method Error Total Con OccSpe MetSpe Rel Implicit Measures Extraversion Anxiety Explicit Measures Extraversion Anxiety Notes. N = 65. Con = Consistency, OccSpe = Occasion Specificity, MetSpe = Method Specificity, Rel = Reliability. a corrected for the total test.

26 IMPLICIT AND EXPLICIT MEASURES 26 Figure Captions Figure 1. Latent state-trait model. The first index of the manifest variables Y refers to the test half, the second to the measurement occasion. O = latent occasion-specific variable, T = latent trait variable. Figure 2. Latent state-trait model with method-specific variances. The first index of the manifest variables Y refers to the test half, the second to the measurement occasion. O = latent occasion-specific variable, T = latent trait variable, M = latent method-specific variable.

27 IMPLICIT AND EXPLICIT MEASURES 27 E 11 Y 11 O 1 T E 21 Y 21 E 12 Y 12 O 2 Y 22 E 22

28 IMPLICIT AND EXPLICIT MEASURES 28 M 1 E 11 Y 11 T T 1 E 21 Y 21 O 1 T 2 E 12 Y 12 O 2 M 2 Y 22 E 22