Investigating heterogeneity in IRTree models for multiple response processes with score-based partitioning.

Item response tree (IRTree) models form a family of psychometric models that allow researchers to control for multiple response processes, such as different sorts of response styles, in the measurement of latent traits. While IRTree models can capture quantitative individual differences in both the latent traits of interest and the use of response categories, they maintain the basic assumption that the nature and weighting of latent response processes are homogeneous across the entire population of respondents. In the present research, we therefore propose a novel approach for detecting heterogeneity in the parameters of IRTree models across subgroups that engage in different response behavior.

Simulation-based design optimization for statistical power: Utilizing machine learning.

The planning of adequately powered research designs increasingly goes beyond determining a suitable sample size. More challenging scenarios demand simultaneous tuning of multiple design parameter dimensions and can only be addressed using Monte Carlo simulation if no analytical approach is available. In addition, cost considerations, for example, in terms of monetary costs, are a relevant target for optimization.

Sample size planning for complex study designs: A tutorial for the mlpwr package.

A common challenge in designing empirical studies is determining an appropriate sample size. When more complex models are used, estimates of power can only be obtained using Monte Carlo simulations. In this tutorial, we introduce the R package mlpwr to perform simulation-based power analysis based on surrogate modeling.

What Affects the Quality of Score Transformations? Potential Issues in True-Score Equating Using the Partial Credit Model.

This simulation study investigated to what extent departures from construct similarity as well as differences in the difficulty and targeting of scales impact the score transformation when scales are equated by means of concurrent calibration using the partial credit model with a common person design. Practical implications of the simulation results are discussed with a focus on scale equating in health-related research settings. The study simulated data for two scales, varying the number of items and the sample sizes.

Interpretable machine learning for psychological research: Opportunities and pitfalls.

In recent years, machine learning methods have become increasingly popular prediction methods in psychology. At the same time, psychological researchers are typically not only interested in making predictions about the dependent variable, but also in learning which predictor variables are relevant, how they influence the dependent variable, and which predictors interact with each other. However, most machine learning methods are not directly interpretable.

A New Stopping Criterion for Rasch Trees Based on the Mantel-Haenszel Effect Size Measure for Differential Item Functioning.

To detect differential item functioning (DIF), Rasch trees search for optimal splitpoints in covariates and identify subgroups of respondents in a data-driven way. To determine whether and in which covariate a split should be performed, Rasch trees use statistical significance tests. Consequently, Rasch trees are more likely to label small DIF effects as significant in larger samples.

Power Analysis for the Wald, LR, Score, and Gradient Tests in a Marginal Maximum Likelihood Framework: Applications in IRT.

The Wald, likelihood ratio, score, and the recently proposed gradient statistics can be used to assess a broad range of hypotheses in item response theory models, for instance, to check the overall model fit or to detect differential item functioning. We introduce new methods for power analysis and sample size planning that can be applied when marginal maximum likelihood estimation is used. This allows the application to a variety of IRT models, which are commonly used in practice, e.

Score-based measurement invariance checks for Bayesian maximum-a-posteriori estimates in item response theory.

A family of score-based tests has been proposed in recent years for assessing the invariance of model parameters in several models of item response theory (IRT). These tests were originally developed in a maximum likelihood framework. This study discusses analogous tests for Bayesian maximum-a-posteriori estimates and multiple-group IRT models.

Engagement With a Mobile Phone-Based Life Skills Intervention for Adolescents and Its Association With Participant Characteristics and Outcomes: Tree-Based Analysis.

Background: Mobile phone-delivered life skills programs are an emerging and promising way to promote mental health and prevent substance use among adolescents, but little is known about how adolescents actually use them.

Objective: The aim of this study is to determine engagement with a mobile phone-based life skills program and its different components, as well as the associations of engagement with adolescent characteristics and intended substance use and mental health outcomes.

Methods: We performed secondary data analysis on data from the intervention group (n=750) from a study that compared a mobile phone-based life skills intervention for adolescents recruited in secondary and upper secondary school classes with an assessment-only control group.

An R toolbox for score-based measurement invariance tests in IRT models.

The detection of differential item functioning (DIF) is a central topic in psychometrics and educational measurement. In the past few years, a new family of score-based tests of measurement invariance has been proposed, which allows the detection of DIF along arbitrary person covariates in a variety of item response theory (IRT) models. This paper illustrates the application of these tests within the R system for statistical computing, making them accessible to a broad range of users.

Development and validation of a patient-reported outcome measure for systemic sclerosis: the EULAR Systemic Sclerosis Impact of Disease (ScleroID) questionnaire.

Objectives: Patient-reported outcome measures (PROMs) are important for clinical practice and research. Given the high unmet need, our aim was to develop a comprehensive PROM for systemic sclerosis (SSc), jointly with patient experts.

Methods: This European Alliance of Associations for Rheumatology (EULAR)-endorsed project involved 11 European SSc centres.

With a little help from familiar interlocutors: real-world language use in young and older adults.

Objectives: Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world.

Testing the Local Independence Assumption of the Rasch Model With -Based Nonparametric Model Tests.

Local independence is a central assumption of commonly used item response theory models. Violations of this assumption are usually tested using test statistics based on item pairs. This study presents two quasi-exact tests based on the statistic for testing the hypothesis of local independence in the Rasch model.

Model Selection of Nested and Non-Nested Item Response Models Using Vuong Tests.

In this paper, we apply Vuong's general approach of model selection to the comparison of nested and non-nested unidimensional and multidimensional item response theory (IRT) models. Vuong's approach of model selection is useful because it allows for formal statistical tests of both nested and non-nested models. However, only the test of non-nested models has been applied in the context of IRT models to date.

Investigating Measurement Invariance by Means of Parameter Instability Tests for 2PL and 3PL Models.

M-fluctuation tests are a recently proposed method for detecting differential item functioning in Rasch models. This article discusses a generalization of this method to two additional item response theory models: the two-parametric logistic model and the three-parametric logistic model with a common guessing parameter. The Type I error rate and the power of this method were evaluated by a variety of simulation studies.

An Evaluation of Overall Goodness-of-Fit Tests for the Rasch Model.

For assessing the fit of item response theory models, it has been suggested to apply overall goodness-of-fit tests as well as tests for individual items and item pairs. Although numerous goodness-of-fit tests have been proposed in the literature for the Rasch model, their relative power against several model violations has not been investigated so far. This study compares four of these tests, which are all available in R software: , , , and the LR test.

Psychobiological Protective Factors Modifying the Association Between Age and Sexual Health in Men: Findings From the Men's Health 40+ Study.

Sexual health severely decreases with age. For males older than 40 years, erectile dysfunction (ED) is the most common sexual disorder. Although physical and psychological risk factors for ED have been identified, protective factors are yet to be determined.

Comparing the Effects of Different Smoothing Algorithms on the Assessment of Dimensionality of Ordered Categorical Items with Parallel Analysis.

The analysis of polychoric correlations via principal component analysis and exploratory factor analysis are well-known approaches to determine the dimensionality of ordered categorical items. However, the application of these approaches has been considered as critical due to the possible indefiniteness of the polychoric correlation matrix. A possible solution to this problem is the application of smoothing algorithms.

Assessing Planning Ability Across the Adult Life Span: Population-Representative and Age-Adjusted Reliability Estimates for the Tower of London (TOL-F).

Planning ahead the consequences of future actions is a prototypical executive function. In clinical and experimental neuropsychology, disc-transfer tasks like the Tower of London (TOL) are commonly used for the assessment of planning ability. Previous psychometric evaluations have, however, yielded a poor reliability of measuring planning performance with the TOL.

Assessment of planning ability: Psychometric analyses on the unidimensionality and construct validity of the Tower of London Task (TOL-F).

Objective: The Tower of London (TOL) is widely used to assess planning ability as a prototypical executive function in healthy and clinical populations. Despite its popularity, there is still no consensus on (a) whether the TOL measures a psychometrically unidimensional trait, and (b) how differences in problem structure relate to the difficulty of individual items.

Method: Employing the framework of factor analysis and item response theory we investigated these issues of construct validity in a sample of 798 participants (443 female; 16 to 84 years).

Intraindividual variability in inhibitory function in adults with ADHD--an ex-Gaussian approach.

Objective: Attention deficit disorder (ADHD) is commonly associated with inhibitory dysfunction contributing to typical behavioral symptoms like impulsivity or hyperactivity. However, some studies analyzing intraindividual variability (IIV) of reaction times in children with ADHD (cADHD) question a predominance of inhibitory deficits. IIV is a measure of the stability of information processing and provides evidence that longer reaction times (RT) in inhibitory tasks in cADHD are due to only a few prolonged responses which may indicate deficits in sustained attention rather than inhibitory dysfunction.