Posterior odds ratios for selected regression hypotheses
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Bayesian posterior odds ratios for frequently encountered hypotheses about parameters of the normal linear multiple regression model are derived and discussed. For the particular prior distributions utilized, it is found that the posterior odds ratios can be well approximated by functions that are monotonic in usual sampling theoryF statistics. Some implications of this finding and the relation of our work to the pioneering work of Jeffreys and others are considered. Tabulations of odds ratios are provided and discussed.
KeywordsBayesian Odds Ratios Hypothesis Testing Regression Hypotheses Regression Model
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