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Shadish, William R.; Rindskopf, David M.; Hedges, Larry V.; Sullivan, Kristynn J. – Online Submission, 2012
Researchers in the single-case design tradition have debated the size and importance of the observed autocorrelations in those designs. All of the past estimates of the autocorrelation in that literature have taken the observed autocorrelation estimates as the data to be used in the debate. However, estimates of the autocorrelation are subject to…
Descriptors: Bayesian Statistics, Research Design, Correlation, Computation
Hedges, Larry V.; Pustejovsky, James E.; Shadish, William R. – Online Submission, 2012
Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on…
Descriptors: Research Design, Effect Size, Meta Analysis, Computation
Rindskopf, David; Shadish, William; Hedges, Larry V. – Online Submission, 2012
This conference presentation demonstrates a multilevel model for analyzing single case designs. The model is implemented in the Bayesian program WinBUGS. The authors show how it is possible to estimate a d-statistic like the one in Hedges, Pustejovsky and Shadish (2012) in this program. Results are demonstrated on an example.
Descriptors: Effect Size, Computation, Hierarchical Linear Modeling, Research Design
Ingels, Steven J. – Online Submission, 2004
This paper addresses two audiences--those who design education trend studies that simultaneously have longitudinal and intercohort implications, and the secondary analysts who use such trend data. Four study series conducted for the U.S. Department of Education's National Center for Education Statistics (NCES) provide material for the paper: the…
Descriptors: Change, Cohort Analysis, Comparative Analysis, Computation