Abstract #302316

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JSM 2003 Abstract #302316
Activity Number: 396
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302316
Title: An Evidential Approach to Hierarchical Models: Does it Make Sense?
Author(s): Subhash R. Lele*+
Companies: University of Alberta
Address: Dept. of Mathematical Sciences, Edmonton, AB, T6G 2G1, Canada
Keywords:
Abstract:

Hierarchical models, traditionally, have been analyzed using either a full Bayesian approach or an empirical Bayes approach. In both cases, the "random effects" are modeled as a realization of a random variable and thus predicted using the conditional distributions. I explore the possibility of considering random effects as unknown but fixed quantities and quantifying evidence for them in terms of the likelihood function. Many times the evidential approach leads to answers that are similar to the empirical Bayes answers; however, the evidential intervals seem to be quite different. The question that does not have a clear answer (at least to me) is: Should we be quantifying "uncertainty" or "evidence" about the random effects? As a particular example, I will analyze the case of "Let's make a deal" from the evidential point of view.

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