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Excerpt from A Fortiori Bayesian Inference in Psychological Research
Bayes Law, or the law of conditional probability, provides a natural inference framework for one who views hypothesis testing as parameter estimation. Heretofore a major difficul ty in applying Bayesian ideas to psychological contexts has been the specification of an objective or public prior. This paper proposes a rule for selecting a prior hypothesis which is both unambiguous and hostile to the research hypothesis: choose the prior so that 1) its expectation is the conventional null value and 2) it has maximum probability of producing the obser ved data. The rule is employed to develop a complete set of tests for nominal data, and both a one-sample and a two-sample.
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A Fortiori Bayesian Inference in Psychological Research (Classic Reprint)
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo LW-9781334538254
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A Fortiori Bayesian Inference in Psychological Research (Classic Reprint)
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo LW-9781334538254
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A Fortiori Bayesian Inference in Psychological Research (Classic Reprint)
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Paperback. Condizione: New. Print on Demand. This book, written by a leading expert in the field, presents an innovative approach to the analysis and interpretation of psychological data using Bayesian theory. Bayesian inference provides a natural framework for hypothesis testing, particularly when the goal is to estimate the strength of a relationship rather than to simply reject the null hypothesis. The author proposes a very conservative way to estimate the strength of a relationship by constraining the prior mean to lie at the conventional null point, and then selecting prior parameters which maximize the likelihood. Such a prior has two interesting features. First, because the argument of the prior is a continuous random variable, the either-or point null is discarded in favor of a âgrayâ diffuse null, whose expectation is the conventional null value of the parameter. Second, by choosing the prior parameters to maximize the constrained likelihood, a null centered prior is defined which has the maximum probability of generating the observed sample data. For a given functional form, the resulting prior stacks the cards against the research hypothesis as much as possible. The inference problem is transformed into computing the probabilistic description of the output parameter, given the sample data. Typically, a random variable is described in terms of the probability that it lies in a small interval. The author develops a variety of tests and illustrates the techniques with numerical examples. This book's insights on applying Bayesian inference to psychological contexts will appeal to advanced undergraduate and graduate students, as well as researchers, in psychology and related fields interested in hypothesis testing and parameter estimation. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Codice articolo 9781334538254_0
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A Fortiori Bayesian Inference in Psychological Research (Classic Reprint)
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Paperback. Condizione: Brand New. 114 pages. 9.02x5.98x0.23 inches. This item is printed on demand. Codice articolo zk1334538255
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