JSM 2004 - Toronto

Abstract #301190

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Activity Number: 89
Type: Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #301190
Title: Using Subpopulation Membership as a Bayesian Diagnostic Technique
Author(s): Guofen Yan*+ and J. Sedransk
Companies: Cleveland Clinic Foundation and Case Western Reserve University
Address: 9500 Euclid Ave., Wb4, Cleveland, OH, 44195,
Keywords: discrepancy ; model assessment ; posterior predictive p value ; test statistic
Abstract:

We investigate the ability of posterior predictive p values to detect unknown hierarchical structure. Since there is limited research in this area we study the simple, but important case where the data come from a two-stage hierarchical regression model while the fitted model does not include this feature. We consider a general class of discrepancy measures (i.e., minimum, maximum, 10th and 90th percentiles, mean, median and standard deviation), which are not motivated by knowledge of the hierarchical structure. We show that diagnostics based on some of the discrepancy measures listed above are not effective when applied to the entire dataset, but such diagnostics are useful when applied to important subpopulations.


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