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Baek, Eunkyeng; Beretvas, S. Natasha; Van den Noortgate, Wim; Ferron, John M. – Journal of Experimental Education, 2020
Recently, researchers have used multilevel models for estimating intervention effects in single-case experiments that include replications across participants (e.g., multiple baseline designs) or for combining results across multiple single-case studies. Researchers estimating these multilevel models have primarily relied on restricted maximum…
Descriptors: Bayesian Statistics, Intervention, Case Studies, Monte Carlo Methods
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Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
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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
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May, Henry – Society for Research on Educational Effectiveness, 2014
Interest in variation in program impacts--How big is it? What might explain it?--has inspired recent work on the analysis of data from multi-site experiments. One critical aspect of this problem involves the use of random or fixed effect estimates to visualize the distribution of impact estimates across a sample of sites. Unfortunately, unless the…
Descriptors: Educational Research, Program Effectiveness, Research Problems, Computation