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Sean Joo; Montserrat Valdivia; Dubravka Svetina Valdivia; Leslie Rutkowski – Journal of Educational and Behavioral Statistics, 2024
Evaluating scale comparability in international large-scale assessments depends on measurement invariance (MI). The root mean square deviation (RMSD) is a standard method for establishing MI in several programs, such as the Programme for International Student Assessment and the Programme for the International Assessment of Adult Competencies.…
Descriptors: International Assessment, Monte Carlo Methods, Statistical Studies, Error of Measurement
Shu, Tian; Luo, Guanzhong; Luo, Zhaosheng; Yu, Xiaofeng; Guo, Xiaojun; Li, Yujun – Journal of Educational and Behavioral Statistics, 2023
Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a…
Descriptors: Cognitive Measurement, Models, Diagnostic Tests, Accuracy
van der Linden, Wim J.; Ren, Hao – Journal of Educational and Behavioral Statistics, 2020
The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee's ability and optimally…
Descriptors: Bayesian Statistics, Adaptive Testing, Error of Measurement, Markov Processes
Monroe, Scott – Journal of Educational and Behavioral Statistics, 2019
In item response theory (IRT) modeling, the Fisher information matrix is used for numerous inferential procedures such as estimating parameter standard errors, constructing test statistics, and facilitating test scoring. In principal, these procedures may be carried out using either the expected information or the observed information. However, in…
Descriptors: Item Response Theory, Error of Measurement, Scoring, Inferences
McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti – Journal of Educational and Behavioral Statistics, 2018
This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…
Descriptors: Hierarchical Linear Modeling, Computer Software, Comparative Analysis, Monte Carlo Methods
Kelcey, Benjamin; Dong, Nianbo; Spybrook, Jessaca; Cox, Kyle – Journal of Educational and Behavioral Statistics, 2017
Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement "what works" questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Mediation Theory, Models
Fan, Weihua; Hancock, Gregory R. – Journal of Educational and Behavioral Statistics, 2012
This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…
Descriptors: Robustness (Statistics), Hypothesis Testing, Monte Carlo Methods, Simulation
Luo, Wen; Kwok, Oi-man – Journal of Educational and Behavioral Statistics, 2012
In longitudinal multilevel studies, especially in educational settings, it is fairly common that participants change their group memberships over time (e.g., students switch to different schools). Participant's mobility changes the multilevel data structure from a purely hierarchical structure with repeated measures nested within individuals and…
Descriptors: Mobility, Statistical Analysis, Models, Longitudinal Studies
Liu, Yuming; Schulz, E. Matthew; Yu, Lei – Journal of Educational and Behavioral Statistics, 2008
A Markov chain Monte Carlo (MCMC) method and a bootstrap method were compared in the estimation of standard errors of item response theory (IRT) true score equating. Three test form relationships were examined: parallel, tau-equivalent, and congeneric. Data were simulated based on Reading Comprehension and Vocabulary tests of the Iowa Tests of…
Descriptors: Reading Comprehension, Test Format, Markov Processes, Educational Testing

Huitema, Bradley E.; And Others – Journal of Educational and Behavioral Statistics, 1996
Monte Carlo study results show that the runs test yields markedly asymmetrical error rates in the two tails and that neither directional nor nondirectional tests are satisfactory with respect to Type I errors. The test is not recommended for evaluating the independence of errors in time-series regression models. (SLD)
Descriptors: Correlation, Error of Measurement, Monte Carlo Methods, Regression (Statistics)
Yuan, Ke-Hai; Maxwell, Scott – Journal of Educational and Behavioral Statistics, 2005
Retrospective or post hoc power analysis is recommended by reviewers and editors of many journals. Little literature has been found that gave a serious study of the post hoc power. When the sample size is large, the observed effect size is a good estimator of the true power. This article studies whether such a power estimator provides valuable…
Descriptors: Effect Size, Computation, Monte Carlo Methods, Bias