Goodness of fit for the logistic regression model using relative belief

• Main Authors: Luai Al-Labadi, Zeynep Baskurt, Michael Evans
• Format: Article
• Language: English
• Published: SpringerOpen 2017-08-01
• Series: Journal of Statistical Distributions and Applications
• Subjects: Model checking; Concentration; Relative belief ratio
• Online Access: http://link.springer.com/article/10.1186/s40488-017-0070-7

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.