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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2020
This article discusses estimation of average treatment effects for randomized controlled trials (RCTs) using grouped administrative data to help improve data access. The focus is on design-based estimators, derived using the building blocks of experiments, that are conducive to grouped data for a wide range of RCT designs, including clustered and…
Descriptors: Randomized Controlled Trials, Data Analysis, Research Design, Multivariate Analysis
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Rhoads, Christopher – Journal of Educational and Behavioral Statistics, 2017
Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Surveys, Effect Size
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Wong, Vivian C.; Steiner, Peter M.; Cook, Thomas D. – Journal of Educational and Behavioral Statistics, 2013
In a traditional regression-discontinuity design (RDD), units are assigned to treatment on the basis of a cutoff score and a continuous assignment variable. The treatment effect is measured at a single cutoff location along the assignment variable. This article introduces the multivariate regression-discontinuity design (MRDD), where multiple…
Descriptors: Computation, Research Design, Regression (Statistics), Multivariate Analysis
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Boik, Robert J. – Journal of Educational and Behavioral Statistics, 1997
An analysis of repeated measures designs is proposed that uses an empirical Bayes estimator of the covariance matrix. The proposed analysis behaves like a univariate analysis when sample size is small or sphericity nearly satisfied, but behaves like multivariate analysis when sample size is large or sphericity is strongly violated. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Multivariate Analysis, Research Design