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James E. Pustejovsky; Man Chen – Journal of Educational and Behavioral Statistics, 2024
Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…
Descriptors: Meta Analysis, Multivariate Analysis, Effect Size, Evaluation Methods
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William R. Dardick; Jeffrey R. Harring – Journal of Educational and Behavioral Statistics, 2025
Simulation studies are the basic tools of quantitative methodologists used to obtain empirical solutions to statistical problems that may be impossible to derive through direct mathematical computations. The successful execution of many simulation studies relies on the accurate generation of correlated multivariate data that adhere to a particular…
Descriptors: Statistics, Statistics Education, Problem Solving, Multivariate Analysis
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Huang, Francis L. – Journal of Educational and Behavioral Statistics, 2022
The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked…
Descriptors: Multivariate Analysis, Computation, Correlation, Error of Measurement
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Waller, Niels G. – Journal of Educational and Behavioral Statistics, 2023
Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…
Descriptors: Statistics Education, Multivariate Analysis, Factor Analysis, Factor Structure
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Francesco Innocenti; Math J. J. M. Candel; Frans E. S. Tan; Gerard J. P. van Breukelen – Journal of Educational and Behavioral Statistics, 2024
Normative studies are needed to obtain norms for comparing individuals with the reference population on relevant clinical or educational measures. Norms can be obtained in an efficient way by regressing the test score on relevant predictors, such as age and sex. When several measures are normed with the same sample, a multivariate regression-based…
Descriptors: Sample Size, Multivariate Analysis, Error of Measurement, Regression (Statistics)
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
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Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2023
In order to evaluate the effect of a policy or treatment with pre- and post-treatment outcomes, we propose an approach based on a transition model, which may be applied with multivariate outcomes and accounts for unobserved heterogeneity. This model is based on potential versions of discrete latent variables representing the individual…
Descriptors: Causal Models, Multivariate Analysis, Markov Processes, Human Capital