Mixture models for continuous data in dose-response studies when some animals are unaffected by treatment.
A mixture model is described for dose-response studies where measurements on a continuous variable suggest that some animals are not affected by treatment. The model combines a logistic regression on dose for the probability an animal will "respond" to treatment with a linear regression on dose for the mean of the responders. Maximum likelihood estimation via the EM algorithm is described and likelihood ratio tests are used to distinguish between the full model and meaningful reduced-parameter versions. Use of the model is illustrated with three real-data examples.
Boos
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Department of Statistics, North Carolina State University, Raleigh 27695-8203.
Brownie
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C
D000465:Algorithms; D000704:Analysis of Variance; D000818:Animals; D001699:Biometry; D004305:Dose-Response Relationship, Drug; D016013:Likelihood Functions; D016015:Logistic Models; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D012044:Regression Analysis