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Wagler, Amy E. – Journal of Educational and Behavioral Statistics, 2014
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
Descriptors: Hierarchical Linear Modeling, Cluster Grouping, Heterogeneous Grouping, Monte Carlo Methods
Wilkins, Chuck; Rolfhus, Eric; Hartman, Jenifer; Brasiel, Sarah; Brite, Jessica; Howland, Noelle – Regional Educational Laboratory Southwest (NJ1), 2012
Many students graduate from high school unprepared for the rigorous reading required in entry-level college and career work. This brief builds on a recent report (Wilkins et al. 2010) that used the Lexile measure (a method for measuring the reading difficulty of prose text and the reading capability of individuals) to estimate the proportion of…
Descriptors: High School Students, Grade 11, Public Education, College English
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2007
A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…
Descriptors: Statistical Significance, Computation, Cluster Grouping, Statistics