Evaluating approximations of Bayesian solutions: the case of Fisher test
(1993) , 22 pages
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- Authors
- Abstract
- In this paper, we evaluate from a Bayesian point of view how much information is lost when the sampling process for the 2x2 contingency table is specified conditionally on the two margins as in the exact test of Fisher. We first analyse the general problem of admissible conditioning and next consider the evaluation of the loss of information when a non-admissible conditioning is used for an approximation of the exact posterior distribution. Turning to the Fisher test, three different sampling models are considered and three comparisons are designed between the exact and the approximate posterior distributions. The numerical results obtained through simulation indicate that for a specific range of parameters the loss of information increases with the sample size and decreases with the precision of the a priori distribution.
- Affiliations
Universidad Austral de Chile Instituto de Informática
Citations
Mouchart, M., & Scheihing, E. (1993). Evaluating approximations of Bayesian solutions: the case of Fisher test (STAT Discussion Papers 9322). https://hdl.handle.net/2078.5/33367