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Comparison to control in logistic regression
Authors:Nairanjana Dasgupta  John D Spurrier  Edward Martinez  Barry C Moore
Institution:1. Program in Statistics , Washington State University , 99164, Pullman, WA;2. Department of Statistics , University of South Carolina , 29208, Columbia, SC;3. Department of Natural Resource Sciences , Washington State University , 99164, Pullman, WA
Abstract:We are interested in comparing logistic regressions for several test treatments or populations with a logistic regression for a standard treatment or population. The research was motivated by some real life problems, which are discussed as data examples. We propose a step-down likelihood ratio method for declaring differences between the test treatments or populations and the standard treatment or population. Competitors based on the sequentially rejective Bonferroni Wald statistic, sequentially rejective exact Wald statistic and Reiers?l's statistic are also discussed. It is shown that the proposed method asymptotically controls the probability of type I error. A Monte Carlo simulation shows that the proposed method performs well for relatively small sample sizes, outperforming its competitors.
Keywords:Binary response  likelihood ratio  maximum likelihood  multivariate chi-square  simultaneous test  step-down  sequentially rejective  marginal power
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