A Predictive Approach to the Analysis of Designed Experiments
- 1 March 1994
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 89 (425) , 309
- https://doi.org/10.2307/2291227
Abstract
Viewing the analysis of designed experiments as a model selection problem, we introduce the use of a predictive Bayesian criterion in this context based on the predictive density of a replicate experiment (PDRE). A calibration of the criterion is provided to assist in the model choice. The relationships of the proposed criterion to other prevalent criteria, such as AIC, BIC, and Mallows's C p , are given. An information theoretic criterion based on the PDRE's of two competing models is also introduced and compared with the usual F statistic for two nested models. Examples are given to illustrate the proposed methodology.Keywords
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