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McNeish, Daniel M.; Stapleton, Laura M. – Educational Psychology Review, 2016
Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Sample Size, Effect Size
Keselman, Joanne C.; And Others – 1993
Meta-analytic methods were used to summarize results of Monte Carlo (MC) studies investigating the robustness of various statistical procedures for testing within-subjects effects in split-plot repeated measures designs. Through a literature review, accessible MC studies were identified, and characteristics (simulation factors) and outcomes (rates…
Descriptors: Computer Simulation, Foreign Countries, Interaction, Least Squares Statistics
Elmore, Patricia B.; Woehlke, Paula L. – 1996
A content analysis was conducted of three educational research journals published by the American Educational Research Association to review the quantitative and qualitative techniques used in educational research. All articles appearing in these three journals from 1988 through 1995 (total n=1,715) were considered. Research methods were…
Descriptors: Analysis of Covariance, Analysis of Variance, Bayesian Statistics, Content Analysis