JSM 2004 - Toronto

Abstract #300138

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Activity Number: 139
Type: Invited
Date/Time: Monday, August 9, 2004 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #300138
Title: Combining Information from Independent Sources through Confidence Distributions
Author(s): Kesar Singh*+ and Minge Xie and William E. Strawderman
Companies: Rutgers University and Rutgers University and Rutgers University
Address: Department of Statistics, Piscataway, NJ, 08854,
Keywords: combining information ; bootstrap ; confidence distribution ; frequentist inference ; p value function ; adaptive meta-analysis
Abstract:

This paper develops a new methodology, together with related theories, to combine informations from independent studies through confidence distributions. It provides a formal version of definition of a confidence distribution and its asymptotic counterpart (i.e., asymptotic confidence distribution), which is convenient for combination purpose. A general combination method is developed along the lines of combining p values, with some notable differences in the optimality part in terms of Bahadur type efficiency. This paper also contains a development of practical interest on adaptive combining methods, with supporting theories provided under large sample settings. The key point of this development is that the adaptive methods combine only the right information, downweighting or excluding studies containing little or wrong information about the true parameter of interest. The combination methodologies are illustrated in three simulated and real data examples with a variety of applications.

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