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Robitzsch, Alexander; Lüdtke, Oliver – Journal of Educational and Behavioral Statistics, 2022
One of the primary goals of international large-scale assessments in education is the comparison of country means in student achievement. This article introduces a framework for discussing differential item functioning (DIF) for such mean comparisons. We compare three different linking methods: concurrent scaling based on full invariance,…
Descriptors: Test Bias, International Assessment, Scaling, Comparative Analysis
Casabianca, Jodi M.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2018
The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance--if the null hypothesis of "no DIF" is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical…
Descriptors: Test Bias, Hypothesis Testing, Bayesian Statistics, Statistical Analysis
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2018
Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel research. In this article, we compare joint modeling (JM) and the fully conditional specification (FCS) of MI as well as different strategies for including auxiliary variables at Level 1 using either their manifest or their latent cluster means. We show with…
Descriptors: Statistical Analysis, Data, Comparative Analysis, Hierarchical Linear Modeling
Kaplan, David; Su, Dan – Journal of Educational and Behavioral Statistics, 2016
This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…
Descriptors: Sampling, Questionnaires, Measurement, International Assessment
Yang, Ji Seung; Zheng, Xiaying – Journal of Educational and Behavioral Statistics, 2018
The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…
Descriptors: Item Response Theory, Item Analysis, Computer Software, Statistical Analysis
Lee, Taehun; Cai, Li – Journal of Educational and Behavioral Statistics, 2012
Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to multiply imputed data sets. However, the presence of multiple random imputations complicates model fit testing, which is an important aspect of mean and covariance structure…
Descriptors: Statistical Inference, Structural Equation Models, Goodness of Fit, Statistical Analysis
Goldstein, Harvey; Bonnet, Gerard; Rocher, Thierry – Journal of Educational and Behavioral Statistics, 2007
The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…
Descriptors: Foreign Countries, Structural Equation Models, Markov Processes, Factor Analysis