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Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R. – Journal of Educational and Behavioral Statistics, 2014
In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…
Descriptors: Hierarchical Linear Modeling, Effect Size, Maximum Likelihood Statistics, Computation
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van Smeden, Maarten; Hessen, David J. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
In this article, a 2-way multigroup common factor model (MG-CFM) is presented. The MG-CFM can be used to estimate interaction effects between 2 grouping variables on 1 or more hypothesized latent variables. For testing the significance of such interactions, a likelihood ratio test is presented. In a simulation study, the robustness of the…
Descriptors: Multivariate Analysis, Robustness (Statistics), Sample Size, Statistical Analysis
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Furgol, Katherine E.; Ho, Andrew D.; Zimmerman, Dale L. – Educational and Psychological Measurement, 2010
Under the No Child Left Behind Act, large-scale test score trend analyses are widespread. These analyses often gloss over interesting changes in test score distributions and involve unrealistic assumptions. Further complications arise from analyses of unanchored, censored assessment data, or proportions of students lying within performance levels…
Descriptors: Trend Analysis, Sample Size, Federal Legislation, Simulation