Problems when fixing the response bias parameter z in drift diffusion analysis : A Commentary on Stafford et al. (2020).

In a simulation study, Stafford et al. (Behavior Research Methods, 52, 2142-2155, 2020) explored the effect of sample size on detecting group differences in ability in the presence of speed-accuracy trade-offs using the Drift Diffusion Model (DDM) and introduced an online tool to perform a power analysis. They found that the DDM approach was superior to analyzing the observed response times and response accuracies alone. In their simulation, they applied the EZ method to estimate the model parameters. In this article, we demonstrate that the EZ method, which cannot estimate the response bias parameter of the DDM, causes severe estimation bias for all parameters if the true response bias is not 0.5. Moreover, the bias patterns differ between EZ and the equivalent maximum likelihood estimation with z fixed at 0.5. This should be taken into consideration when using the otherwise excellent power analysis tool for experimental designs, in which z≠ 0.5 cannot be ruled out or even stipulate it.

The diffusion model visualizer: an interactive tool to understand the diffusion model parameters.

Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates seven parameters, the roles of which are difficult to comprehend from the model equation. Therefore, the present article introduces the diffusion model visualizer (DMV) allowing for interactive manipulation of each parameter and plotting the resulting RT densities. Thus, the DMV serves as a valuable tool for understanding the specific role of each model parameter. It may come in handy for didactical purposes and in research context. It allows for tracking down parameter estimation problems by delivering the model-based ideal densities, which can be juxtaposed to the data-based densities. It will also serve a valuable purpose in detecting outliers. The article describes the basics of the DM along with technical details of the DMV and gives several hints for its usage.

The blenderFace method: video-based measurement of raw movement data during facial expressions of emotion using open-source software.

This article proposes an optical measurement of movement applied to data from video recordings of facial expressions of emotion. The approach offers a way to capture motion adapted from the film industry in which markers placed on the skin of the face can be tracked with a pattern-matching algorithm. The method records and postprocesses raw facial movement data (coordinates per frame) of distinctly placed markers and is intended for use in facial expression research (e.g., microexpressions) in laboratory settings. Due to the explicit use of specifically placed, artificial markers, the procedure offers the simultaneous measurement of several emotionally relevant markers in a (psychometrically) objective and artifact-free way, even for facial regions without natural landmarks (e.g., the cheeks). In addition, the proposed procedure is fully based on open-source software and is transparent at every step of data processing. Two worked examples demonstrate the practicability of the proposed procedure: In Study 1(N= 39), the participants were instructed to show the emotions happiness, sadness, disgust, and anger, and in Study 2 (N= 113), they were asked to present both a neutral face and the emotions happiness, disgust, and fear. Study 2 involved the simultaneous tracking of 14 markers for approximately 12 min per participant with a time resolution of 33 ms. The measured facial movements corresponded closely to the assumptions of established measurement instruments (EMFACS, FACSAID, Friesen & Ekman, 1983; Ekman & Hager, 2002). In addition, the measurement was found to be very precise with sub-second, sub-pixel, and sub-millimeter accuracy.

Dimensionality of the Russian CORE-OM from a Rasch Perspective.

The evaluation of outcomes in mental health care embraces evaluation, quality assurance, and progress measurement of treatments. The Clinical Outcome in Routine Evaluation - Outcome Measure (CORE-OM) is an outcome focused self-assessment instrument, comprising 34 items covering four scales well-being, problems, functioning, and risk. The questionnaire has been translated into 52 languages, including Russian. Despite its broad application, the dimensionality of the CORE-OM deserves some further research. Thus, the present study examines the dimensionality of the Russian CORE-OM using the multidimensional random coefficients multinomial logit model (MRCMLM) based on data of N = 240 patients. The results indicate the need for further research on factorial structure and response formats of the CORE-OM. In addition, differential item functioning was found for gender and diagnostic groups, suggesting separate test norms. Again, the MRCMLM and the Test Analysis Modules (TAM) package have proven valuable tools for investigating a questionnaire's psychometric properties.

[A psychometric view on the applicability of the BDI-II in non-clinical populations]. / Die Anwendbarkeit des BDI-II in klinischen und nichtklinischen Populationen aus psychometrischer Sicht. Eine vergleichende Analyse mit dem Rasch-Modell.

BACKGROUND: The revised version of the Beck Depression Inventory (BDI-II) is a broadly used instrument for assessing the severity of depression of adolescents of at least 13 years of age and adults. The self-assessment questionnaire contains 21 polytomous items and follows the criteria for a major depression specified in the DSM-IV. Clinical samples have often been used to analyze the psychometric properties of the instrument primarily with factor analytic methods. METHODS: The present study performs a psychometric analysis in a non-clinical sample in order to ascertain, whether the instrument performs equally well with the different kinds of samples. A clinical sample and a sample of students filled in the questionnaire. A partial credit model was applied and parameter estimates and model fit of the two samples were compared. RESULTS: Threshold parameters and model fit largely agreed, however some items exhibited characteristic deviations. Nevertheless, person parameter estimates notably agreed in both samples. CONCLUSIONS: These results indicate that the BDI-II performs in clinical and non-clinical samples comparably well, only some items show characteristic deviations in the non-clinical sample.

Benefits of the Curious Behavior of Bayesian Hierarchical Item Response Theory Models-An in-Depth Investigation and Bias Correction.

When using Bayesian hierarchical modeling, a popular approach for Item Response Theory (IRT) models, researchers typically face a tradeoff between the precision and accuracy of the item parameter estimates. Given the pooling principle and variance-dependent shrinkage, the expected behavior of Bayesian hierarchical IRT models is to deliver more precise but biased item parameter estimates, compared to those obtained in nonhierarchical models. Previous research, however, points out the possibility that, in the context of the two-parameter logistic IRT model, the aforementioned tradeoff has not to be made. With a comprehensive simulation study, we provide an in-depth investigation into this possibility. The results show a superior performance, in terms of bias, RMSE and precision, of the hierarchical specifications compared to the nonhierarchical counterpart. Under certain conditions, the bias in the item parameter estimates is independent of the bias in the variance components. Moreover, we provide a bias correction procedure for item discrimination parameter estimates. In sum, we show that IRT models create a unique situation where the Bayesian hierarchical approach indeed yields parameter estimates that are not only more precise, but also more accurate, compared to nonhierarchical approaches. We discuss this beneficial behavior from both theoretical and applied point of views.

The Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF): German Translation and Psychometric Assessment.

BACKGROUND: German-speaking mothers have breastfeeding rates below the international breastfeeding recommendations. Previous research has found that breastfeeding self-efficacy is an important and modifiable predictor of breastfeeding outcomes, thus improving breastfeeding rates. The Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) is used in many countries to assess maternal breastfeeding self-efficacy. This instrument has not been available in German. RESEARCH AIMS: To translate the BSES-SF into German and assess its psychometric properties among breastfeeding mothers up to 12 weeks postpartum. METHODS: This cross-sectional study was conducted online with 355 breastfeeding mothers recruited from breastfeeding groups through Facebook. The BSES-SF was translated into German using forward and back-translation. To test reliability, item-total characteristics, including Cronbach's alpha, were examined. We used principal component analysis, as well as known-groups comparisons for evaluating construct validity, and examined the relationship between breastfeeding self-efficacy and demographic variables. RESULTS: The mean age of participants was 32.4 years (SD = 4.32). The Cronbach's alpha coefficient was .88 and corrected item-total correlations ranged between .37 and .73. Principal components analysis yielded one component with factor loadings >.40 and an eigenvalue of 5.62, which explained 40% of the total variance. In addition, known group comparisons provided further evidence for construct validity. There was no significant difference in BSES-SF scores in terms of demographic and obstetrics characteristics. CONCLUSION: Our results provide evidence that the German version of the BSES-SF is a reliable and valid tool for measuring breastfeeding self-efficacy among mothers in German-speaking countries.

Strengths and weaknesses of the German translation of the Inflexible Eating Questionnaire and of eating disorder assessment in general.

Objective: The present article introduces the German translation of the Inflexible Eating Questionnaire (IEQ-G), performs a psychometric evaluation, and explores the relationship of Inflexible Eating to the subscales of the Eating Disorder Examination-Questionnaire (EDE-Q) and Obsessive-Compulsive (OC) symptoms. Methods: The cross-sectional study was carried out in the German-speaking area. A paper and pencil survey was completed by 612 females and 442 males of the general population. Results: SEM analyses showed that the IEQ-G allows for calculating a total score and invariance tests were mostly promising. As a side result, the original 4-factorial structure of the EDE-Q could not be replicated, but a 3 dimensional solution proved convincing. From a psychometric point of view, the IEQ-G outperformed the EDE-Q. On a latent level, Inflexible Eating was remarkably strong related to OC-symptoms and the EDE-Q subscales. Discussion: The detail analyses revealed that Eating Disorder assessment in general lacks subgroup-specific aspects, for instance, regarding gender or dietary preferences, important for early diagnosis and screening of ED. The IEQ-G proved applicable in a German speaking adult population and recommends itself for cross-cultural studies.

Determinants of quality of life improvements in anxiety and depressive disorders-A longitudinal study of inpatient psychotherapy.

Background: Quality of life (QoL) is substantially impaired in patients with anxiety disorders (AD) and depressive disorders (DD) and improvements in symptom burden after psychotherapy are not always paralleled by similar improvements in QoL. So far, little is known about treatment outcome in terms of QoL and predictors of QoL improvements following inpatient psychotherapy with a focus on cognitive behavior therapy (CBT). The current study aimed at investigating the relationship between changes in symptoms and QoL across different life domains. Additionally, predictors of a positive treatment outcome were evaluated. Methods: 122 patients with AD and/or DD undergoing an 8-weeks inpatient CBT program completed self-report measures of psychopathological symptoms and QoL at pre- and post-treatment. Mixed effects models were used to investigate changes, a confirmatory factor analysis was applied to analyze the latent factor structure of the anxiety sensitivity index and binary logistic regression analyses were performed for predictors of QoL improvements. Results: Patients showed moderate to strong decreases in anxious and depressive symptoms and moderate to strong improvements in general QoL, particularly in the psychological and physical QoL subdomains. Changes in symptom burden correlated most strongly with psychological and physical QoL. In addition, poor QoL before treatment and low levels of specific anxiety sensitivity symptoms (items 1 and 5) significantly predicted improvement in QoL. Conclusion: Patients with poor QoL who are not as inhibited to openly express their anxious feelings particularly benefit from inpatient psychotherapy (individual and group) to improve their QoL. In contrast, our research suggests that patients who are too anxious to openly express their nervousness should receive additional social skills training, more focused treatment to build sufficient self-confidence to better engage in the treatment program.

Comparing Eight Parameter Estimation Methods for the Ratcliff Diffusion Model Using Free Software.

The Ratcliff Diffusion Model has become an important and widely used tool for the evaluation of psychological experiments. Concurrently, numerous programs and routines have appeared to estimate the model's parameters. The present study aims at comparing some of the most widely used tools with special focus on freely available routines (i.e., open source). Our simulations show that (1) starting point and non-decision time were recovered better than drift rate, (2) the Bayesian approach outperformed all other approaches when the number of trials was low, (3) the Kolmogorov-Smirnov and χ2 approaches revealed more bias than Bayesian or Maximum Likelihood based routines, and (4) EZ produced substantially biased estimates of threshold separation, non-decision time and drift rate when starting point z ≠ a/2. We discuss the implications for the choice of parameter estimation approaches for real data and suggest that if biased starting point cannot be excluded, EZ will produce deviant estimates and should be used with great care.

Comparing outcomes: The Clinical Outcome in Routine Evaluation from an international point of view.

OBJECTIVES: The Clinical Outcome in Routine Evaluation-Outcome Measure (CORE-OM) is a freely accessible self-assessment questionnaire with a total of 34 items measuring the progress of psychological or psychotherapeutic treatments according to four scales (well-being, problems, functioning, and risk). The CORE-OM originated in the United Kingdom and has been translated into 54 languages and dialects. The aim of this study is to systematically compare the translated versions. METHOD: A total of 21 translations were compared using methods of systematic review and meta-analysis. RESULTS: The results show a certain heterogeneity between the studies; however, the 21 translations can be declared as equivalent. CONCLUSION: The factorial structure could not be replicated in any of translations. Therefore, further analysis of the CORE-OM domains is recommended. In addition, some supplementary restrictions on the translation process, data collection, and reporting of results are necessary to ensure comparability and quality of CORE-OM translations.

Sampling and weighting of the Austrian Psychiatric Prevalence Survey (APPS).

Mental disorders are common and have severe consequences for the patients, their relatives, and society. Mental health care planning requires precise knowledge of the prevalence of psychiatric disorders and details regarding the provided treatment. Because administrative data lack information on persons not in contact with health services, we need epidemiologic studies delivering nationwide information on the prevalence of psychiatric disorders. This requirement induces the need for adequate sampling procedures to collect reliable data, allowing for accurate estimations of mental health care needs, over- and underprovision. This is the purpose of the Austrian Psychiatric Prevalence Survey (APPS).The present technical report describes the exact procedure how a nationwide sample has been drawn, adopting a stratified cluster sampling scheme. Because such a complex sampling procedure requires an adequate weighting to obtain unbiased population estimates, this report also contains the exact steps to calculate the corresponding weights. This way, the report not only fosters the full disclosure of the sampling strategy of the APPS, it may also serve as a best practice example for similar endeavours.

[Criterion Validity of the 15-item Geriatric Depression Scale in the Austrian Population]. / Die Kriteriumsvalidität der 15-Item Geriatrischen Depressionsskala in der österreichischen Bevölkerung.

OBJECTIVE: The "Geriatric Depression Scale" consisting of 15 items (GDS-15) is a well-known screening tool for depression among the elderly. Until now the criterion validity of the German language GDS-15 was not investigated in a sample of the adult general population. METHODS: 504 persons of the Austrian general population completed the GDS-15. Using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) ICD-10 diagnoses were established. Receiver Operating Characteristics (ROC) analysis was conducted. Possible gender and age differences were explored. RESULTS: The overall discrimination of the GDS-15 was sufficient (ROC-AUC 0,851). The cut-off value developed on the basis of our sample was 2/3 with a sensitivity of 71.8 % und a specificity of 82.8 %. We could not find significant gender or age group differences. CONCLUSION: This is the first study investigating the criterion validity of the German language GDS-15 in the adult general population. The sensitivity and specificity are sufficient and comparable with the findings among other screening tools.

Assessing the dimensionality of the CES-D using multi-dimensional multi-level Rasch models.

OBJECTIVES: The CES-D is a widely used depression screening instrument. While numerous studies have analysed its psychometric properties using exploratory and various kinds of confirmatory factor analyses, only few studies used Rasch models and none a multidimensional one. METHODS: The present study applies a multidimensional Rasch model using a sample of 518 respondents representative for the Austrian general population aged 18 to 65. A one-dimensional model, a four-dimensional model reflecting the subscale structure suggested by [1], and a four-dimensional model with the background variables gender and age were applied. RESULTS: While the one-dimensional model showed relatively good fit, the four-dimensional model fitted much better. EAP reliability indices were generally satisfying and the latent correlations varied between 0.31 and 0.88. In the analysis involving background variables, we found a limited effect of the participants' gender. DIF effects were found unveiling some peculiarities. The two-items subscale Interpersonal Difficulties showed severe weaknesses and the Positive Affect subscale with the reversed item wordings also showed unexpected results. CONCLUSIONS: While a one-dimensional over-all score might still contain helpful information, the differentiation according to the latent dimension is strongly preferable. Altogether, the CES-D can be recommended as a screening instrument, however, some modifications seem indicated.

[Criterion Validity of the German Version of the CES-D in the General Population]. / Kriteriumsvalidität der deutschsprachigen Version der CES-D in der Allgemeinbevölkerung.

OBJECTIVE: The "Center of Epidemiologic Studies - Depression scale" (CES-D) is a well-known screening tool for depression. Until now the criterion validity of the German version of the CES-D was not investigated in a sample of the adult general population. METHODS: 508 study participants of the Austrian general population completed the CES-D. ICD-10 diagnoses were established by using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN). Receiver Operating Characteristics (ROC) analysis was conducted. Possible gender differences were explored. RESULTS: Overall discriminating performance of the CES-D was sufficient (ROC-AUC 0,836). Using the traditional cut-off values of 15/16 and 21/22 respectively the sensitivity was 43.2 % and 32.4 %, respectively. The cut-off value developed on the basis of our sample was 9/10 with a sensitivity of 81.1 % und a specificity of 74.3 %. There were no significant gender differences. CONCLUSION: This is the first study investigating the criterion validity of the German version of the CES-D in the general population. The optimal cut-off values yielded sufficient sensitivity and specificity, comparable to the values of other screening tools.

Successful emotion regulation is predicted by amygdala activity and aspects of personality: A latent variable approach.

The experience of emotions and their cognitive control are based upon neural responses in prefrontal and subcortical regions and could be affected by personality and temperamental traits. Previous studies established an association between activity in reappraisal-related brain regions (e.g., inferior frontal gyrus and amygdala) and emotion regulation success. Given these relationships, we aimed to further elucidate how individual differences in emotion regulation skills relate to brain activity within the emotion regulation network on the one hand, and personality/temperamental traits on the other. We directly examined the relationship between personality and temperamental traits, emotion regulation success and its underlying neuronal network in a large sample (N = 82) using an explicit emotion regulation task and functional MRI (fMRI). We applied a multimethodological analysis approach, combing standard activation-based analyses with structural equation modeling. First, we found that successful downregulation is predicted by activity in key regions related to emotion processing. Second, the individual ability to successfully upregulate emotions is strongly associated with the ability to identify feelings, conscientiousness, and neuroticism. Third, the successful downregulation of emotion is modulated by openness to experience and habitual use of reappraisal. Fourth, the ability to regulate emotions is best predicted by a combination of brain activity and personality as well temperamental traits. Using a multimethodological analysis approach, we provide a first step toward a causal model of individual differences in emotion regulation ability by linking biological systems underlying emotion regulation with descriptive constructs. (PsycINFO Database Record

The importance of statistical modelling in clinical research : Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients.

BACKGROUND: Various studies have shown that caregiving relatives of schizophrenic patients are at risk of suffering from depression. These studies differ with respect to the applied statistical methods, which could influence the findings. Therefore, the present study analyzes to which extent different methods may cause differing results. METHODS: The present study contrasts by means of one data set the results of three different modelling approaches, Rasch Modelling (RM), Structural Equation Modelling (SEM), and Linear Regression Modelling (LRM). RESULTS: The results of the three models varied considerably, reflecting the different assumptions of the respective models. CONCLUSIONS: Latent trait models (i. e., RM and SEM) generally provide more convincing results by correcting for measurement error and the RM specifically proves superior for it treats ordered categorical data most adequately.

[Depression Symptoms of Mothers and Fathers of Persons with Schizophrenia]. / Die Depressivität von Müttern und Vätern von Schizophreniekranken.

OBJECTIVE: The purpose of the present study was to investigate if depression symptomatology of patients' parents is predicted by the symptoms of schizophrenia. METHODS: 101 mothers and 101 fathers of the same patients suffering from schizophrenia were included into this study. Parents filled in the "Beck Depression Inventory". Patients were assessed by means of the "Positive and Negative Syndrome Scale". For statistical analyses a Multidimensional Random Coefficients Multinomial Logit Model was applied. RESULTS: We found a significant positive association between negative symptoms and depression severity of fathers and mothers. Further, a significant positive association between positive symptoms and depression severity of fathers, but not of mothers was found. CONCLUSION: Our results show that depression of mothers and of fathers is associated with symptoms of schizophrenia even when controlling for potential predictors.

Sample Size Determination Within the Scope of Conditional Maximum Likelihood Estimation with Special Focus on Testing the Rasch Model.

This paper refers to the exponential family of probability distributions and the conditional maximum likelihood (CML) theory. It is concerned with the determination of the sample size for three groups of tests of linear hypotheses, known as the fundamental trinity of Wald, score, and likelihood ratio tests. The main practical purpose refers to the special case of tests of the class of Rasch models. The theoretical background is discussed and the formal framework for sample size calculations is provided, given a predetermined deviation from the model to be tested and the probabilities of the errors of the first and second kinds.