Goodness of fit for the logistic regression model using relative belief

Luai Al-Labadi (), Zeynep Baskurt () and Michael Evans ()
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Luai Al-Labadi: University of Toronto
Zeynep Baskurt: Genetics and Genome Biology, Hospital for Sick Children
Michael Evans: University of Toronto

Journal of Statistical Distributions and Applications, 2017, vol. 4, issue 1, 1-12

Abstract: Abstract A logistic regression model is a specialized model for product-binomial data. When a proper, noninformative prior is placed on the unrestricted model for the product-binomial model, the hypothesis H 0 of a logistic regression model holding can then be assessed by comparing the concentration of the posterior distribution about H 0 with the concentration of the prior about H 0. This comparison is effected via a relative belief ratio, a measure of the evidence that H 0 is true, together with a measure of the strength of the evidence that H 0 is either true or false. This gives an effective goodness of fit test for logistic regression.

Keywords: Model checking; Concentration; Relative belief ratio; 62F15 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1186/s40488-017-0070-7

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