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Hedges, Larry V.; Schauer, Jacob M. – Journal of Educational and Behavioral Statistics, 2019
The problem of assessing whether experimental results can be replicated is becoming increasingly important in many areas of science. It is often assumed that assessing replication is straightforward: All one needs to do is repeat the study and see whether the results of the original and replication studies agree. This article shows that the…
Descriptors: Replication (Evaluation), Research Design, Research Methodology, Program Evaluation
Hedges, Larry V.; Borenstein, Michael – Journal of Educational and Behavioral Statistics, 2014
The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to…
Descriptors: Experiments, Research Design, Sample Size, Correlation
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
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2011
Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…
Descriptors: Effect Size, Research Design, Experiments, Computation
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2009
A common mistake in analysis of cluster randomized experiments 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.…
Descriptors: Data Analysis, Statistical Significance, Statistics, Experiments
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2007
Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…
Descriptors: Journal Articles, Effect Size, Computation, Research Design