Department of Statistics, The Ohio State University
Statistics and Biostatistics Colloquium Series

The ANOVA models are common in analyzing data from a wide range of areas such as biology, psychology, and sociology. Two versions exist in literature, namely the fixed effect model and the random effect model. The main difference of these two types of models lies in whether or not the effects of the factor levels are treated as random variables. In practice, however, there are many cases where it is not clear whether or not the factor effects should be treated as fixed or random. Moreover, from the Bayesian point of view, all parameters are considered as random variables, making the distinction between fixed effect model and random effect model rather obscure. The primary goal of this talk is to seek for a unified Bayesian approach to deal with one-way ANOVA models with fixed effects and random effects. We propose a modification of the Zellner-Siow prior, and show that the proposed prior will result in good frequentist properties in terms of model selection in the settings of either fixed or random effect.

Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.