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Killeen, Peter R. – Psychological Methods, 2010
Lecoutre, Lecoutre, and Poitevineau (2010) have provided sophisticated grounding for "p[subscript rep]." Computing it precisely appears, fortunately, no more difficult than doing so approximately. Their analysis will help move predictive inference into the mainstream. Iverson, Wagenmakers, and Lee (2010) have also validated…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Design, Research Methodology
Cumming, Geoff – Psychological Methods, 2010
This comment offers three descriptions of "p[subscript rep]" that start with a frequentist account of confidence intervals, draw on R. A. Fisher's fiducial argument, and do not make Bayesian assumptions. Links are described among "p[subscript rep]," "p" values, and the probability a confidence interval will capture…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Methodology, Validity
Peer reviewedFischhoff, Baruch; Beyth-Marom, Ruth – Psychological Review, 1983
This article explores the potential of Bayesian inference as a theoretical framework for describing how people evaluate hypotheses. First, it identifies a set of logically possible forms of non-Bayesian behavior. Second, it reviews existing research in a variety of areas to see whether these possibilities are ever realized. (Author/BW)
Descriptors: Bayesian Statistics, Bias, Experimenter Characteristics, Hypothesis Testing
Peer reviewedMcClure, John; Suen, Hoi K. – Topics in Early Childhood Special Education, 1994
This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…
Descriptors: Bayesian Statistics, Early Childhood Education, Educational Research, Hypothesis Testing

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