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Society for Research on Educational Effectiveness, 2013
One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…
Descriptors: Research Design, Effect Size, Intervention, Statistical Analysis
Rindskopf, David; Shadish, William; Hedges, Larry – Society for Research on Educational Effectiveness, 2012
Data from single case designs (SCDs) have traditionally been analyzed by visual inspection rather than statistical models. As a consequence, effect sizes have been of little interest. Lately, some effect-size estimators have been proposed, but most are either (i) nonparametric, and/or (ii) based on an analogy incompatible with effect sizes from…
Descriptors: Intervention, Effect Size, Bayesian Statistics, Research Design
Swaminathan, Hariharan; Horner, Robert H.; Rogers, H. Jane; Sugai, George – Society for Research on Educational Effectiveness, 2012
This study is aimed at addressing the criticisms that have been leveled at the currently available statistical procedures for analyzing single subject designs (SSD). One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been…
Descriptors: Evidence, Effect Size, Research Methodology, Intervention
Camilli, Gregory; de la Torre, Jimmy; Chiu, Chia-Yi – Journal of Educational and Behavioral Statistics, 2010
In this article, three multilevel models for meta-analysis are examined. Hedges and Olkin suggested that effect sizes follow a noncentral "t" distribution and proposed several approximate methods. Raudenbush and Bryk further refined this model; however, this procedure is based on a normal approximation. In the current research literature, this…
Descriptors: Markov Processes, Effect Size, Meta Analysis, Monte Carlo Methods

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