André Beauducel - Academia.edu (original) (raw)

Papers by André Beauducel

Frontiers in Human Neuroscience, Apr 11, 2014

Personality and Individual Differences, Mar 1, 2017

Frontiers in Psychology, Nov 26, 2023

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant... more Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique simple structure. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimize effects of sampling error on results of Targetrotation we propose to compute the mean cross-loadings for each block of salient loadings of the independent clusters model and to perform Target-rotation for the block-wise mean cross-loadings. The resulting transformation-matrix is than applied to the complete unrotated loading matrix in order to produce mean Target-rotated factors. Results: A simulation study based on correlated independent clusters model and zero-mean cross-loading models revealed that mean oblique Target-rotation resulted in smaller bias of factor inter-correlations than conventional Targetrotation based on single loadings, especially when sample size was small and when the number of factors was large. An empirical example revealed that the similarity of Target-rotated factors computed for small subsamples with Targetrotated factors of the total sample was more pronounced for mean Targetrotation than for conventional Target-rotation. Discussion: Mean Target-rotation can be recommended in the context of oblique factor models based on simple structure, especially for small samples. An R-script and an SPSS-script for this form of Target-rotation are provided in the Supplementary Material.

Alternate-forms reliability; Coefficient of equivalence; Parallel-test reliability Definition Par... more Alternate-forms reliability; Coefficient of equivalence; Parallel-test reliability Definition Parallel forms of a test are different subsets of the same universe of items, which capture the same attribute with the same accuracy. As a measurement model for the scores of parallel forms, (strict) parallel measures are assumed, so that the correlation between the scores, i.e., the parallelforms reliability or parallel-test reliability matches the reliability of both forms.

Communications in Statistics, Apr 1, 2015

Anderson and Rubin (1956), as well as Takeuchi et al. (1982) finally Schneeweiss and Mathes (1995... more Anderson and Rubin (1956), as well as Takeuchi et al. (1982) finally Schneeweiss and Mathes (1995) proposed factor score predictors that were regarded as orthogonal. Anderson and Rubin's and Takeuchi et al.'s factor score predictors are shown to be identical for non zero unique variances, although they have never been claimed being identical. It is shown that the Schneeweiss and Mathe's factor score predictor is not equal to McDonald's factor score predictor, although it has been claimed that these predictors are identical. It is, moreover, shown that the Schneeweiss and Mathe's factor score predictor is orthogonal only for the canonical orthogonal factor model.

Biological Psychology, May 1, 2021

Many studies on concealed knowledge involve mock-thefts. The present study compares ERPs of parti... more Many studies on concealed knowledge involve mock-thefts. The present study compares ERPs of participants concealing knowledge of a morally negative behavior (mock-theft) with ERPs of participants concealing knowledge of a morally positive behavior. Some participants (n= 33) stole a candy box out of an office, whereas others (n= 28) put the candy box into an office as a present. During a concealed information test, participants concealed knowledge of the candy box and a key they had seen in the office (probe stimuli) and honestly indicated not knowing similar irrelevant stimuli. P300 s were enlarged for probe, compared to irrelevant stimuli in both conditions, revealing that probe stimuli were more salient than irrelevant stimuli regardless of their moral valence. Likewise, medial frontal negativities were enlarged for probe versus irrelevant stimuli in both conditions, indicating response conflicts when answering deceptively to probe items in both situations.

Social Cognitive and Affective Neuroscience, Aug 1, 2020

Event-related potential (ERP) studies about deception often apply recognition tasks. It remains q... more Event-related potential (ERP) studies about deception often apply recognition tasks. It remains questionable whether reported ERP patterns and cognitive processes can be generalized to other contexts. As the study by Johnson et al. (2008) fills this gap by investigating deception regarding attitudes, we tried to replicate it. Participants (N = 99) were instructed to lie or tell the truth about their attitudes. We obtained the same results as Johnson et al. (2008): lies were accompanied by enhanced medial frontal negativities (MFN) and suppressed late positive components (LPCs) indicating that lying relied on stronger cognitive control processes and response conf licts than being honest. The amplitudes of pre-response positivities (PRP) were reduced for lies implying that lies about attitudes were accompanied by strategic monitoring. MFN amplitudes increased and LPC amplitudes decreased for lies about positively valued items revealing that lying about positively valued items is cognitively more challenging than lying about negatively valued items. As a new finding, MFN, LPC and PRP components were neither moderated by Machiavellianism nor by changes in the attitude ratings. The results indicate that LPC, MFN and PRP components are reliable indicators of the cognitive processes used during deception and that it is worthwhile to investigate them in further deception contexts.

International Journal of Psychophysiology, Mar 1, 2019

Although the association of the N2 component with behavioral inhibition (BIS) has regularly been ... more Although the association of the N2 component with behavioral inhibition (BIS) has regularly been investigated, its association with other personality characteristics remains widely unknown. We investigated the association of the N2 with the sensitivity of the behavioral activation system (BAS). The aim was not to show that the N2 is linked to trait BAS instead of trait BIS, but that a motivating setting may alter its association with those traits. Furthermore, we aimed at replicating results indicating that the association between reasoning ability and the N2 depends on the matching of the content of the reasoning tasks and the go-nogo task. The electroencephalogram (64 electrodes, P9/P10 offline reference, Biosemi) was recorded in a sample of 117 healthy participants (60 females; age: M = 24.79, SD = 3.98), who performed a numerical learning task. At the beginning of each trial, participants heard motivating or neutral words. Participants completed Carver and White's BIS/BAS scales (1994) and the Intelligence-Structure-Test 2000R (Liepmann et al., 2007). The N2 was identified by a temporospatial principal component analysis. Structural equation models revealed that higher trait BAS scores were associated with larger N2s especially when hearing motivating words. Solely higher numerical reasoning scores were associated with larger N2s in the neutral condition. Moreover, the interaction of trait BAS with verbal reasoning ability predicted an increased negativity of the N2 with time-on-task in the motivating condition, suggesting that motivating words yielded an increase of conflict monitoring with time-on-task for participants with higher verbal reasoning ability and higher trait BAS.

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences, 2005

. Because of factor score indeterminacy, there can be substantial shifts in the theoretical meani... more . Because of factor score indeterminacy, there can be substantial shifts in the theoretical meaning of factors and their corresponding score estimates. Therefore, the original factor pattern should be compared with the regression-component loadings (Schönemann & Steiger, 1976) corresponding to the factor-score estimates in order to detect possible shifts in the theoretical meaning. Especially with large loading matrices the similarity of the original factor pattern and the regression components of the score estimates may be ascertained by means of congruency coefficients. It is shown that these congruencies contain information that is not already given by measures of factor-score indeterminacy. Two examples illustrate the use of regression-component analysis for different types of factor-score estimates. The analyses reveal that the Bartlett-score estimates are most appropriate when factor interpretation is based on the factor pattern, which is usually the case in confirmatory factor analysis.

arXiv (Cornell University), Apr 24, 2018

To derive recommendations on how to analyze longitudinal data, we examined Type I error rates of ... more To derive recommendations on how to analyze longitudinal data, we examined Type I error rates of Multilevel Linear Models (MLM) and repeated measures Analysis of Variance (rANOVA) using SAS and SPSS. We performed a simulation with the following specifications: To explore the effects of high numbers of measurement occasions and small sample sizes on Type I error, measurement occasions of m = 9 and 12 were investigated as well as sample sizes of n = 15, 20, 25 and 30. Effects of non-sphericity in the population on Type I error were also inspected: 5,000 random samples were drawn from two populations containing neither a within-subject nor a between-group effect. They were analyzed including the most common options to correct rANOVA and MLM-results: The Huynh-Feldt-correction for rANOVA (rANOVA-HF) and the Kenward-Roger-correction for MLM (MLM-KR), which could help to correct progressive bias of MLM with an unstructured covariance matrix (MLM-UN). Moreover, uncorrected rANOVA and MLM assuming a compound symmetry covariance structure (MLM-CS) were also taken into account. The results showed a progressive bias for MLM-UN for small samples which was stronger in SPSS than in SAS. Moreover, an appropriate bias correction for Type I error via rANOVA-HF and an insufficient correction by MLM-UN-KR for n < 30 were found. These findings suggest MLM-CS or rANOVA if sphericity holds and a correction of a violation via rANOVA-HF. If an analysis requires MLM, SPSS yields more accurate Type I error rates for MLM-CS and SAS yields more accurate Type I error rates for MLM-UN.

... Beauducel, André and Biehl, Bernhard and Bosnjak, Michael and Conrad, Wolfgang and Schönberge... more ... Beauducel, André and Biehl, Bernhard and Bosnjak, Michael and Conrad, Wolfgang and Schönberger, Gisela and Wagener, Dietrich (2005 ... Analysis", primarily the statistical aspects of multivariate research will be addressed (Oberauer, Wilhelm & Schmiedek; Walach & Kohls ...

Cognitive, Affective, & Behavioral Neuroscience, Feb 15, 2012

According to Botvinick's (Cognitive, Affective, & Behavioral Neuroscience 7, 356-366, 2007) integ... more According to Botvinick's (Cognitive, Affective, & Behavioral Neuroscience 7, 356-366, 2007) integrative account, conflict monitoring is aversive because individuals anticipate cognitive demand, whereas the revised reinforcement sensitivity theory (rRST) predicts that conflict processing is aversive because individuals anticipate aversive reinforcement of erroneous responses. Because these accounts give different reasons for the aversive aspects of conflict, we manipulated cognitive demand and the aversive reinforcement as a consequence of wrong choices in a go/no-go task. Thereby, we also aimed to investigate whether individual differences in conflict sensitivity (i.e., in trait anxiety, linked to high sensitivity of the behavioral inhibition system [trait-BIS]) represent the effects of aversive reinforcement and cognitive demand in conflict tasks. We expected that these manipulations would have effects on the frontal N2 component representing activity of the anterior cingulate cortex. Moreover, higher-trait-BIS individuals should be more sensitive than lower-trait-BIS individuals to aversive effects in conflict situations, resulting in a more negative frontal N2 for higher-trait-BIS individuals. In Study 1, with N 0 104 students, and Study 2, with N 0 47 students, aversive reinforcement was manipulated in three levels (within-subjects factor) and cognitive demand in two levels (between-subjects factor). The behavioral findings from the go/no-go task with noncounterbalanced reinforcement levels (Study 1) could be widely replicated in a task with counterbalanced reinforcement levels (Study 2). The frontal mean no-go N2 amplitude and the frontal no-go N2 dipole captured predicted reinforcement-related variations of conflict monitoring, indicating that the anticipation of aversive reinforcement induces variations in conflict monitoring intensity in frontal brain areas. The aversive nature of conflict was underlined by the more pronounced conflict monitoring in higher-than in lowertrait-BIS individuals.

arXiv (Cornell University), Jul 11, 2023

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant... more Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique independent clusters model. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimize effects of sampling error on results of Target-rotation we propose to compute the mean cross-loadings for each block of salient loadings of the independent clusters model and to perform target rotation for the block-wise mean cross-loadings. The resulting transformation-matrix is than applied to the complete unrotated loading matrix in order to produce mean Target-rotated factors. Results: A simulation study based on correlated independent factor models revealed that mean oblique Target-rotation resulted in smaller negative bias of factor inter-correlations than conventional Target-rotation based on single loadings, especially when sample size was small and when the number of factors was large. An empirical example revealed that the similarity of Target-rotated factors computed for small subsamples with Target-rotated factors of the total sample was more pronounced for mean Target-rotation than for conventional Target-rotation. Discussion: Mean Target-rotation can be recommended in the context of oblique independent factor models, especially for small samples. An R-script and an SPSS-script for this form of Target-rotation are provided in the Appendix.

arXiv (Cornell University), Apr 19, 2018

The allocation of a (treatment) condition-effect on the wrong principal component (misallocation ... more The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-level is a necessary condition for an optimal allocation of between-condition variance, whereas a similar loading magnitude is not necessary.

Frontiers in Psychology, Aug 11, 2022

The ERN-Ne of the event-related potential indicates error monitoring. Even though enlarged ERN-Ne... more The ERN-Ne of the event-related potential indicates error monitoring. Even though enlarged ERN-Ne amplitudes have often been related to higher anxiety scores, a recent meta-analysis provided very small effect sizes for the association of trait-anxiety with the ERN-Ne. Conditions modulating this association were investigated in the present study: (1) The generality of the trait-anxiety factor, (2) gender, and (3) experimental conditions, i.e., worry induction and error aversiveness. Participants (48% men) completed a flanker task. Worries were induced before the task by giving participants (n = 61) a bogus feedback claiming their responses were slower than the average responses of participants, whereas other participants (n = 61) got the feedback that they responded as fast as other participants. Aversiveness of errors was varied by playing sinus tones after too slow responses in one part of the task (no-scream condition) and aversive screams after too slow responses in another part (scream condition). Increased ERN-Ne amplitudes of response time errors occurred for individuals higher on trait-anxiety in the condition with induced worries and screams. A multiple group model for women and men indicated that women are more sensitive to conditions altering the association of trait-anxiety with the ERN-Ne.

Encyclopedia of Psychological Assessment, Oct 5, 2012

Educational and Psychological Measurement, Jan 5, 2021

Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. Ho... more Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading matrices may be rank deficient when the salient loadings of each factor have the same sign. It was shown here that full-rank two-facet loading matrices are, in principle, possible, when some factors have positive and negative salient loadings. Accordingly, the current simulation study on the number of factors to extract for two-facet models was based on rank-deficient and full-rank two-facet population models. The number of factors to extract was estimated from traditional parallel analysis based on the mean of the unreduced eigenvalues as well as from nine other rather traditional versions of parallel analysis (based on the 95th percentile of eigenvalues, based on reduced eigenvalues, based on eigenvalue differences). Parallel analysis based on the mean eigenvalues of the correlation matrix with the squared multiple correlations of each variable with the remaining variables inserted in the main diagonal had the highest detection rates for most of the two-facet factor models. Recommendations for the identification of the correct number of factors are based on the simulation results, on the results of an empirical example data set, and on the conditions for approximately rank-deficient and full-rank two-facet models.

arXiv (Cornell University), Sep 20, 2021

In the context of Bayesian factor analysis, it is possible to compute mean plausible values, whic... more In the context of Bayesian factor analysis, it is possible to compute mean plausible values, which might be used as covariates or predictors or in order to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of the plausible values by the mean squared difference of the plausible values and the generating factor scores. However, the generating factor scores are unknown in empirical studies so that an indicator that is solely based on model parameters is needed in order to evaluate the validity of factor score estimates in empirical studies. The coefficient of determinacy is based on model parameters and can be computed whenever Bayesian factor analysis is performed in empirical settings. Therefore, the central aim of the present simulation study was to compare the coefficient of determinacy based on model parameters with the correlation of mean plausible values with the generating factors. It was found that the coefficient of determinacy yields an acceptable estimate for the validity of mean plausible values. As for small sample sizes and a small salient loading size the coefficient of determinacy overestimates the validity, it is recommended to report the coefficient of determinacy together with a bias-correction in order to estimate the validity of mean plausible values in empirical settings.

Frontiers in Human Neuroscience, Apr 11, 2014

Personality and Individual Differences, Mar 1, 2017

Frontiers in Psychology, Nov 26, 2023

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant... more Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique simple structure. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimize effects of sampling error on results of Targetrotation we propose to compute the mean cross-loadings for each block of salient loadings of the independent clusters model and to perform Target-rotation for the block-wise mean cross-loadings. The resulting transformation-matrix is than applied to the complete unrotated loading matrix in order to produce mean Target-rotated factors. Results: A simulation study based on correlated independent clusters model and zero-mean cross-loading models revealed that mean oblique Target-rotation resulted in smaller bias of factor inter-correlations than conventional Targetrotation based on single loadings, especially when sample size was small and when the number of factors was large. An empirical example revealed that the similarity of Target-rotated factors computed for small subsamples with Targetrotated factors of the total sample was more pronounced for mean Targetrotation than for conventional Target-rotation. Discussion: Mean Target-rotation can be recommended in the context of oblique factor models based on simple structure, especially for small samples. An R-script and an SPSS-script for this form of Target-rotation are provided in the Supplementary Material.

Alternate-forms reliability; Coefficient of equivalence; Parallel-test reliability Definition Par... more Alternate-forms reliability; Coefficient of equivalence; Parallel-test reliability Definition Parallel forms of a test are different subsets of the same universe of items, which capture the same attribute with the same accuracy. As a measurement model for the scores of parallel forms, (strict) parallel measures are assumed, so that the correlation between the scores, i.e., the parallelforms reliability or parallel-test reliability matches the reliability of both forms.

Communications in Statistics, Apr 1, 2015

Anderson and Rubin (1956), as well as Takeuchi et al. (1982) finally Schneeweiss and Mathes (1995... more Anderson and Rubin (1956), as well as Takeuchi et al. (1982) finally Schneeweiss and Mathes (1995) proposed factor score predictors that were regarded as orthogonal. Anderson and Rubin's and Takeuchi et al.'s factor score predictors are shown to be identical for non zero unique variances, although they have never been claimed being identical. It is shown that the Schneeweiss and Mathe's factor score predictor is not equal to McDonald's factor score predictor, although it has been claimed that these predictors are identical. It is, moreover, shown that the Schneeweiss and Mathe's factor score predictor is orthogonal only for the canonical orthogonal factor model.

Biological Psychology, May 1, 2021

Many studies on concealed knowledge involve mock-thefts. The present study compares ERPs of parti... more Many studies on concealed knowledge involve mock-thefts. The present study compares ERPs of participants concealing knowledge of a morally negative behavior (mock-theft) with ERPs of participants concealing knowledge of a morally positive behavior. Some participants (n= 33) stole a candy box out of an office, whereas others (n= 28) put the candy box into an office as a present. During a concealed information test, participants concealed knowledge of the candy box and a key they had seen in the office (probe stimuli) and honestly indicated not knowing similar irrelevant stimuli. P300 s were enlarged for probe, compared to irrelevant stimuli in both conditions, revealing that probe stimuli were more salient than irrelevant stimuli regardless of their moral valence. Likewise, medial frontal negativities were enlarged for probe versus irrelevant stimuli in both conditions, indicating response conflicts when answering deceptively to probe items in both situations.

Social Cognitive and Affective Neuroscience, Aug 1, 2020

Event-related potential (ERP) studies about deception often apply recognition tasks. It remains q... more Event-related potential (ERP) studies about deception often apply recognition tasks. It remains questionable whether reported ERP patterns and cognitive processes can be generalized to other contexts. As the study by Johnson et al. (2008) fills this gap by investigating deception regarding attitudes, we tried to replicate it. Participants (N = 99) were instructed to lie or tell the truth about their attitudes. We obtained the same results as Johnson et al. (2008): lies were accompanied by enhanced medial frontal negativities (MFN) and suppressed late positive components (LPCs) indicating that lying relied on stronger cognitive control processes and response conf licts than being honest. The amplitudes of pre-response positivities (PRP) were reduced for lies implying that lies about attitudes were accompanied by strategic monitoring. MFN amplitudes increased and LPC amplitudes decreased for lies about positively valued items revealing that lying about positively valued items is cognitively more challenging than lying about negatively valued items. As a new finding, MFN, LPC and PRP components were neither moderated by Machiavellianism nor by changes in the attitude ratings. The results indicate that LPC, MFN and PRP components are reliable indicators of the cognitive processes used during deception and that it is worthwhile to investigate them in further deception contexts.

International Journal of Psychophysiology, Mar 1, 2019

Although the association of the N2 component with behavioral inhibition (BIS) has regularly been ... more Although the association of the N2 component with behavioral inhibition (BIS) has regularly been investigated, its association with other personality characteristics remains widely unknown. We investigated the association of the N2 with the sensitivity of the behavioral activation system (BAS). The aim was not to show that the N2 is linked to trait BAS instead of trait BIS, but that a motivating setting may alter its association with those traits. Furthermore, we aimed at replicating results indicating that the association between reasoning ability and the N2 depends on the matching of the content of the reasoning tasks and the go-nogo task. The electroencephalogram (64 electrodes, P9/P10 offline reference, Biosemi) was recorded in a sample of 117 healthy participants (60 females; age: M = 24.79, SD = 3.98), who performed a numerical learning task. At the beginning of each trial, participants heard motivating or neutral words. Participants completed Carver and White's BIS/BAS scales (1994) and the Intelligence-Structure-Test 2000R (Liepmann et al., 2007). The N2 was identified by a temporospatial principal component analysis. Structural equation models revealed that higher trait BAS scores were associated with larger N2s especially when hearing motivating words. Solely higher numerical reasoning scores were associated with larger N2s in the neutral condition. Moreover, the interaction of trait BAS with verbal reasoning ability predicted an increased negativity of the N2 with time-on-task in the motivating condition, suggesting that motivating words yielded an increase of conflict monitoring with time-on-task for participants with higher verbal reasoning ability and higher trait BAS.

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences, 2005

. Because of factor score indeterminacy, there can be substantial shifts in the theoretical meani... more . Because of factor score indeterminacy, there can be substantial shifts in the theoretical meaning of factors and their corresponding score estimates. Therefore, the original factor pattern should be compared with the regression-component loadings (Schönemann &amp; Steiger, 1976) corresponding to the factor-score estimates in order to detect possible shifts in the theoretical meaning. Especially with large loading matrices the similarity of the original factor pattern and the regression components of the score estimates may be ascertained by means of congruency coefficients. It is shown that these congruencies contain information that is not already given by measures of factor-score indeterminacy. Two examples illustrate the use of regression-component analysis for different types of factor-score estimates. The analyses reveal that the Bartlett-score estimates are most appropriate when factor interpretation is based on the factor pattern, which is usually the case in confirmatory factor analysis.

arXiv (Cornell University), Apr 24, 2018

To derive recommendations on how to analyze longitudinal data, we examined Type I error rates of ... more To derive recommendations on how to analyze longitudinal data, we examined Type I error rates of Multilevel Linear Models (MLM) and repeated measures Analysis of Variance (rANOVA) using SAS and SPSS. We performed a simulation with the following specifications: To explore the effects of high numbers of measurement occasions and small sample sizes on Type I error, measurement occasions of m = 9 and 12 were investigated as well as sample sizes of n = 15, 20, 25 and 30. Effects of non-sphericity in the population on Type I error were also inspected: 5,000 random samples were drawn from two populations containing neither a within-subject nor a between-group effect. They were analyzed including the most common options to correct rANOVA and MLM-results: The Huynh-Feldt-correction for rANOVA (rANOVA-HF) and the Kenward-Roger-correction for MLM (MLM-KR), which could help to correct progressive bias of MLM with an unstructured covariance matrix (MLM-UN). Moreover, uncorrected rANOVA and MLM assuming a compound symmetry covariance structure (MLM-CS) were also taken into account. The results showed a progressive bias for MLM-UN for small samples which was stronger in SPSS than in SAS. Moreover, an appropriate bias correction for Type I error via rANOVA-HF and an insufficient correction by MLM-UN-KR for n < 30 were found. These findings suggest MLM-CS or rANOVA if sphericity holds and a correction of a violation via rANOVA-HF. If an analysis requires MLM, SPSS yields more accurate Type I error rates for MLM-CS and SAS yields more accurate Type I error rates for MLM-UN.

... Beauducel, André and Biehl, Bernhard and Bosnjak, Michael and Conrad, Wolfgang and Schönberge... more ... Beauducel, André and Biehl, Bernhard and Bosnjak, Michael and Conrad, Wolfgang and Schönberger, Gisela and Wagener, Dietrich (2005 ... Analysis", primarily the statistical aspects of multivariate research will be addressed (Oberauer, Wilhelm & Schmiedek; Walach & Kohls ...

Cognitive, Affective, & Behavioral Neuroscience, Feb 15, 2012

According to Botvinick's (Cognitive, Affective, & Behavioral Neuroscience 7, 356-366, 2007) integ... more According to Botvinick's (Cognitive, Affective, & Behavioral Neuroscience 7, 356-366, 2007) integrative account, conflict monitoring is aversive because individuals anticipate cognitive demand, whereas the revised reinforcement sensitivity theory (rRST) predicts that conflict processing is aversive because individuals anticipate aversive reinforcement of erroneous responses. Because these accounts give different reasons for the aversive aspects of conflict, we manipulated cognitive demand and the aversive reinforcement as a consequence of wrong choices in a go/no-go task. Thereby, we also aimed to investigate whether individual differences in conflict sensitivity (i.e., in trait anxiety, linked to high sensitivity of the behavioral inhibition system [trait-BIS]) represent the effects of aversive reinforcement and cognitive demand in conflict tasks. We expected that these manipulations would have effects on the frontal N2 component representing activity of the anterior cingulate cortex. Moreover, higher-trait-BIS individuals should be more sensitive than lower-trait-BIS individuals to aversive effects in conflict situations, resulting in a more negative frontal N2 for higher-trait-BIS individuals. In Study 1, with N 0 104 students, and Study 2, with N 0 47 students, aversive reinforcement was manipulated in three levels (within-subjects factor) and cognitive demand in two levels (between-subjects factor). The behavioral findings from the go/no-go task with noncounterbalanced reinforcement levels (Study 1) could be widely replicated in a task with counterbalanced reinforcement levels (Study 2). The frontal mean no-go N2 amplitude and the frontal no-go N2 dipole captured predicted reinforcement-related variations of conflict monitoring, indicating that the anticipation of aversive reinforcement induces variations in conflict monitoring intensity in frontal brain areas. The aversive nature of conflict was underlined by the more pronounced conflict monitoring in higher-than in lowertrait-BIS individuals.

arXiv (Cornell University), Jul 11, 2023

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant... more Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique independent clusters model. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimize effects of sampling error on results of Target-rotation we propose to compute the mean cross-loadings for each block of salient loadings of the independent clusters model and to perform target rotation for the block-wise mean cross-loadings. The resulting transformation-matrix is than applied to the complete unrotated loading matrix in order to produce mean Target-rotated factors. Results: A simulation study based on correlated independent factor models revealed that mean oblique Target-rotation resulted in smaller negative bias of factor inter-correlations than conventional Target-rotation based on single loadings, especially when sample size was small and when the number of factors was large. An empirical example revealed that the similarity of Target-rotated factors computed for small subsamples with Target-rotated factors of the total sample was more pronounced for mean Target-rotation than for conventional Target-rotation. Discussion: Mean Target-rotation can be recommended in the context of oblique independent factor models, especially for small samples. An R-script and an SPSS-script for this form of Target-rotation are provided in the Appendix.

arXiv (Cornell University), Apr 19, 2018

The allocation of a (treatment) condition-effect on the wrong principal component (misallocation ... more The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-level is a necessary condition for an optimal allocation of between-condition variance, whereas a similar loading magnitude is not necessary.

Frontiers in Psychology, Aug 11, 2022

The ERN-Ne of the event-related potential indicates error monitoring. Even though enlarged ERN-Ne... more The ERN-Ne of the event-related potential indicates error monitoring. Even though enlarged ERN-Ne amplitudes have often been related to higher anxiety scores, a recent meta-analysis provided very small effect sizes for the association of trait-anxiety with the ERN-Ne. Conditions modulating this association were investigated in the present study: (1) The generality of the trait-anxiety factor, (2) gender, and (3) experimental conditions, i.e., worry induction and error aversiveness. Participants (48% men) completed a flanker task. Worries were induced before the task by giving participants (n = 61) a bogus feedback claiming their responses were slower than the average responses of participants, whereas other participants (n = 61) got the feedback that they responded as fast as other participants. Aversiveness of errors was varied by playing sinus tones after too slow responses in one part of the task (no-scream condition) and aversive screams after too slow responses in another part (scream condition). Increased ERN-Ne amplitudes of response time errors occurred for individuals higher on trait-anxiety in the condition with induced worries and screams. A multiple group model for women and men indicated that women are more sensitive to conditions altering the association of trait-anxiety with the ERN-Ne.

Encyclopedia of Psychological Assessment, Oct 5, 2012

Educational and Psychological Measurement, Jan 5, 2021

Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. Ho... more Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading matrices may be rank deficient when the salient loadings of each factor have the same sign. It was shown here that full-rank two-facet loading matrices are, in principle, possible, when some factors have positive and negative salient loadings. Accordingly, the current simulation study on the number of factors to extract for two-facet models was based on rank-deficient and full-rank two-facet population models. The number of factors to extract was estimated from traditional parallel analysis based on the mean of the unreduced eigenvalues as well as from nine other rather traditional versions of parallel analysis (based on the 95th percentile of eigenvalues, based on reduced eigenvalues, based on eigenvalue differences). Parallel analysis based on the mean eigenvalues of the correlation matrix with the squared multiple correlations of each variable with the remaining variables inserted in the main diagonal had the highest detection rates for most of the two-facet factor models. Recommendations for the identification of the correct number of factors are based on the simulation results, on the results of an empirical example data set, and on the conditions for approximately rank-deficient and full-rank two-facet models.

arXiv (Cornell University), Sep 20, 2021

In the context of Bayesian factor analysis, it is possible to compute mean plausible values, whic... more In the context of Bayesian factor analysis, it is possible to compute mean plausible values, which might be used as covariates or predictors or in order to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of the plausible values by the mean squared difference of the plausible values and the generating factor scores. However, the generating factor scores are unknown in empirical studies so that an indicator that is solely based on model parameters is needed in order to evaluate the validity of factor score estimates in empirical studies. The coefficient of determinacy is based on model parameters and can be computed whenever Bayesian factor analysis is performed in empirical settings. Therefore, the central aim of the present simulation study was to compare the coefficient of determinacy based on model parameters with the correlation of mean plausible values with the generating factors. It was found that the coefficient of determinacy yields an acceptable estimate for the validity of mean plausible values. As for small sample sizes and a small salient loading size the coefficient of determinacy overestimates the validity, it is recommended to report the coefficient of determinacy together with a bias-correction in order to estimate the validity of mean plausible values in empirical settings.