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Asymptotic Posterior Normality of Multivariate Latent Traits in an IRT Model
The asymptotic posterior normality (APN) of the latent variable vector in an item response theory (IRT) model is a crucial argument in IRT modeling...
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The effect of latent and error non-normality on corrections to the test statistic in structural equation modeling
In structural equation modeling, several corrections to the likelihood-ratio model test statistic have been developed to counter the effects of...
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Detecting Latent Variable Non-normality Through the Generalized Hausman Test
This paper extends the generalized Hausman test to detect non-normality of the latent variable distribution in unidimensional IRT models for binary...
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Examining the normality assumption of a design-comparable effect size in single-case designs
What Works Clearinghouse (WWC,
2022 ) recommends a design-comparable effect size (D-CES; i.e., g AB ) to gauge an intervention in single-case...
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Pooling test statistics across multiply imputed datasets for nonnormal items
In structural equation modeling, when multiple imputation is used for handling missing data, model fit evaluation involves pooling likelihood-ratio...
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Partial Identification of Latent Correlations with Ordinal Data
The polychoric correlation is a popular measure of association for ordinal data. It estimates a latent correlation, i.e., the correlation of a latent...
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Frequentist Model Averaging in Structure Equation Model With Ordinal Data
In practice, it is common that a best fitting structural equation model (SEM) is selected from a set of candidate SEMs and inference is conducted...
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Non-parametric Regression Among Factor Scores: Motivation and Diagnostics for Nonlinear Structural Equation Models
We provide a framework for motivating and diagnosing the functional form in the structural part of nonlinear or linear structural equation models...
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Assumptions of the Normal Error Regression Model
This chapter describes the main assumptions that are made in the derivation of regression-based normative data, i.e., equality of the error...
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A comparison of multiple imputation strategies to deal with missing nonnormal data in structural equation modeling
Missing data and nonnormality are two common factors that can affect analysis results from structural equation modeling (SEM). The current study aims...
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Are your random effects normal? A simulation study of methods for estimating whether subjects or items come from more than one population by examining the distribution of random effects in mixed-effects logistic regression
With mixed-effects regression models becoming a mainstream tool for every psycholinguist, there has become an increasing need to understand them more...
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Optimizing Large-Scale Educational Assessment with a “Divide-and-Conquer” Strategy: Fast and Efficient Distributed Bayesian Inference in IRT Models
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes...
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Measures of Agreement with Multiple Raters: Fréchet Variances and Inference
Most measures of agreement are chance-corrected. They differ in three dimensions: their definition of chance agreement, their choice of disagreement...
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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...
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The Asymptotic Distribution of Average Test Overlap Rate in Computerized Adaptive Testing
The average test overlap rate is often computed and reported as a measure of test security risk or item pool utilization of a computerized adaptive...
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Simultaneous estimation of the intermediate correlation matrix for arbitrary marginal densities
A popular approach to the simulation of multivariate, non-normal data in the social sciences is to define a multivariate normal distribution first,...
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A unified model-implied instrumental variable approach for structural equation modeling with mixed variables
The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of structural equation models that is more robust to...
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Researcher degrees of freedom in statistical software contribute to unreliable results: A comparison of nonparametric analyses conducted in SPSS, SAS, Stata, and R
Researcher degrees of freedom can affect the results of hypothesis tests and consequently, the conclusions drawn from the data. Previous research has...
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Robust Inference for Mediated Effects in Partially Linear Models
We consider mediated effects of an exposure, X on an outcome, Y , via a mediator, M , under no unmeasured confounding assumptions in the setting where...
