74 hasil untuk "Alexander Robitzsch"
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Artikel Jurnal
Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods
The analysis of factor structures is one of the most critical psychometric applications. Frequently, variables (i.e., items or indicators) resulting from questionnaires using ordinal items with 2–7 categories are used. There are plenty of articles that recommend treating ordinal variables in a…
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Does random differential item functioning occur in one or two groups? Implications for bias and variance in asymmetric and symmetric Haebara and Stocking-Lord linking
Linking methods are frequently applied to analyze the performance of two groups on a set of items. This article shows analytically and by simulation that the occurrence of differential item functioning (DIF) can induce bias and additional variance in parameter estimates of the linking method…
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A Note on Tutz’s Pairwise Separation Estimator
The Rasch model has the desirable property that item parameter estimation can be separated from person parameter estimation. This implies that no assumptions about the ability distribution are required when estimating item difficulties. Pairwise estimation approaches in the Rasch model exploit this…
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Bias Reduction in Robust Mean–Geometric Mean Linking via SIMEX
Robust mean–geometric mean (MGM) linking is a method for comparing the performance of two groups on a test involving dichotomous items and is particularly suited to settings with fixed and sparse differential item functioning (DIF). However, robust MGM linking has been shown to yield biased…
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A Comparison of Mixed and Partial Membership Diagnostic Classification Models with Multidimensional Item Response Models
Diagnostic classification models (DCM) are latent structure models with discrete multivariate latent variables. Recently, extensions of DCMs to mixed membership have been proposed. In this article, ordinary DCMs, mixed and partial membership models, and multidimensional item response theory (IRT)…
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About the Equivalence of the Latent D-Scoring Model and the Two-Parameter Logistic Item Response Model
This article shows that the recently proposed latent D-scoring model of Dimitrov is statistically equivalent to the two-parameter logistic item response model. An analytical derivation and a numerical illustration are employed for demonstrating this finding. Hence, estimation techniques for the…
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Estimation Methods of the Multiple-Group One-Dimensional Factor Model: Implied Identification Constraints in the Violation of Measurement Invariance
Factor analysis is one of the most important statistical tools for analyzing multivariate data (i.e., items) in the social sciences. An essential case is the comparison of multiple groups on a one-dimensional factor variable that can be interpreted as a summary of the items. The assumption of…
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Comparing Robust Linking and Regularized Estimation for Linking Two Groups in the 1PL and 2PL Models in the Presence of Sparse Uniform Differential Item Functioning
In the social sciences, the performance of two groups is frequently compared based on a cognitive test involving binary items. Item response models are often utilized for comparing the two groups. However, the presence of differential item functioning (DIF) can impact group comparisons. In order to…
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Analytical Approximation of the Jackknife Linking Error in Item Response Models Utilizing a Taylor Expansion of the Log-Likelihood Function
Linking errors in item response models quantify the dependence on the chosen items in means, standard deviations, or other distribution parameters. The jackknife approach is frequently employed in the computation of the linking error. However, this jackknife linking error could be computationally…
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Regularized Latent Class Analysis for Polytomous Item Responses: An Application to SPM-LS Data
The last series of Raven’s standard progressive matrices (SPM-LS) test was studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCMs). For dichotomous item response data, an alternative…
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Assessing Standard Error Estimation Approaches for Robust Mean-Geometric Mean Linking
Robust mean-geometric mean (MGM) linking methods enable reliable group comparisons in item response theory models under fixed and sparse differential item functioning. This article evaluates six alternative standard error and confidence interval (CI) estimation methods across four MGM linking…
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Comparing Weighted RMSD, Weighted MD, Infit, and Outfit Item Fit Statistics Under Uniform Differential Item Functioning
In educational large-scale assessment studies, uniform differential item functioning (DIF) across countries often challenges the application of a common item response model, such as the two-parameter logistic (2PL) model, to all participating countries. DIF occurs when certain items provide…
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Implementation Aspects in Regularized Structural Equation Models
This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non-differentiable penalty functions perform…
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Estimating Local Structural Equation Models
Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of…
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To Check or Not to Check? A Comment on the Contemporary Psychometrics (ConPsy) Checklist for the Analysis of Questionnaire Items
In a recent paper, the first version of the contemporary psychometrics (ConPsy) checklist for assessing measurement tool quality has been published. This checklist aims to provide guidelines and references to researchers to assess measurement properties for newly developed measurement instruments…
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L0 and Lp Loss Functions in Model-Robust Estimation of Structural Equation Models
The Lp loss function has been used for model-robust estimation of structural equation models based on robustly fitting moments. This article addresses the choice of the tuning parameter ε that appears in the differentiable approximations of the nondifferentiable Lp loss functions. Moreover…
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Editorial of the Psych Special Issue “Computational Aspects, Statistical Algorithms and Software in Psychometrics”
Statistical software in psychometrics has made tremendous progress in providing open source solutions (e [...]
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Relating the Ramsay Quotient Model to the Classical D-Scoring Rule
In a series of papers, Dimitrov suggested the classical D-scoring rule for scoring items that give difficult items a higher weight while easier items receive a lower weight. The latent D-scoring model has been proposed to serve as a latent mirror of the classical D-scoring model. However, the item…
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Relating the One-Parameter Logistic Diagnostic Classification Model to the Rasch Model and One-Parameter Logistic Mixed, Partial, and Probabilistic Membership Diagnostic Classification Models
Diagnostic classification models (DCMs) are statistical models with discrete latent variables (so-called skills) to analyze multiple binary variables (i.e., items). The one-parameter logistic diagnostic classification model (1PLDCM) is a DCM with one skill and shares desirable measurement…