Information identities and testing hypotheses : power analysis for contingency tables
Cheng, Philip E., Liou, Michelle, Aston, John A. D. and Tsai, Arthur C.. (2008) Information identities and testing hypotheses : power analysis for contingency tables. Statistica Sinica, Vol.18 (No.2). pp. 535-558. ISSN 1017-0405Full text not available from this repository.
An information theoretic approach to the evaluation of 2 x 2 contingency tables is proposed. By investigating the relationship between the Kullback-Leibler divergence and the maximum likelihood estimator, information identities are established for testing hypotheses, in particular, for testing independence. These identities not only validate the calibration of p values, but also yield a unified power analysis for the likelihood ratio test, Fisher's exact test and the Pearson-Yates chi-square test. It is shown that a widely discussed exact unconditional test for the equality of binomial parameters is ill-posed for testing independence, and that using this test to criticize Fisher's exact test as being conservative is logically flawed.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics|
|Divisions:||Faculty of Science > Statistics|
|Library of Congress Subject Headings (LCSH):||Contingency tables, Chi-square test, Statistical hypothesis testing|
|Journal or Publication Title:||Statistica Sinica|
|Publisher:||Academia Sinica, Institute of Statistical Science|
|Official Date:||April 2008|
|Number of Pages:||24|
|Page Range:||pp. 535-558|
|Access rights to Published version:||Restricted or Subscription Access|
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