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Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P. N. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Individuals draw conclusions about possibilities from assertions that make no explicit reference to them. The model theory postulates that assertions such as disjunctions refer to possibilities. Hence, a disjunction of the sort, "A or B or both," where "A" and "B" are sensible clauses, yields mental models of an…
Descriptors: Logical Thinking, Abstract Reasoning, Inferences, Probability
Vanpaemel, Wolf; Lee, Michael D. – Psychological Bulletin, 2012
Wills and Pothos (2012) reviewed approaches to evaluating formal models of categorization, raising a series of worthwhile issues, challenges, and goals. Unfortunately, in discussing these issues and proposing solutions, Wills and Pothos (2012) did not consider Bayesian methods in any detail. This means not only that their review excludes a major…
Descriptors: Classification, Program Evaluation, Bayesian Statistics, Models
Griffiths, Thomas L.; Chater, Nick; Norris, Dennis; Pouget, Alexandre – Psychological Bulletin, 2012
Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific…
Descriptors: Bayesian Statistics, Psychology, Brain, Models
Mislevy, Robert J. – Measurement: Interdisciplinary Research and Perspectives, 2012
Paul E. Newton's "Clarifying the Consensus Definition of Validity" addresses the single most important, yet stubbornly protean, value in educational and psychological assessment. "Standards for Educational and Psychological Testing" (American Educational Research Association, American Psychological Association, & National Council on Measurement in…
Descriptors: Evidence, Validity, Educational Testing, Psychological Evaluation
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
Griffiths, Thomas L.; Tenenbaum, Joshua B. – Cognition, 2007
People's reactions to coincidences are often cited as an illustration of the irrationality of human reasoning about chance. We argue that coincidences may be better understood in terms of rational statistical inference, based on their functional role in processes of causal discovery and theory revision. We present a formal definition of…
Descriptors: Probability, Statistical Inference, Bayesian Statistics, Theories
Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
This paper comments on the response offered by Trafimow on Lee and Wagenmakers comments on Trafimow's original article. It seems our comment should have made it clear that the objective Bayesian approach we advocate views probabilities neither as relative frequencies nor as belief states, but as degrees of plausibility assigned to propositions in…
Descriptors: Researchers, Probability, Statistical Inference, Bayesian Statistics
Trafimow, David – Psychological Review, 2005
In their comment on D. Trafimow, M. D. Lee and E. Wagenmakers argued that the requisite probabilities to use in Bayes's theorem can always be found. In the present reply, the author asserts that M. D. Lee and E. Wagenmakers use a problematic assumption and that finding the requisite probabilities is not straightforward. After describing the…
Descriptors: Probability, Bayesian Statistics, Error Patterns, Criticism

Fischhoff, 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
Thorndike, Robert L. – 1980
In an invitational address to the Victorian Institute of Educational Research, the author discussed Bayesian theory and its relationship to the design and construction of tailored or adaptive tests. Bayesian thinking involves recognizing the role of prior probabilities and using these probabilities in combination with new data to arrive at future…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Error of Measurement