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当一些动物不受治疗影响时,剂量反应研究中连续数据的混合模型。

Mixture models for continuous data in dose-response studies when some animals are unaffected by treatment.

作者信息

Boos D D, Brownie C

机构信息

Department of Statistics, North Carolina State University, Raleigh 27695-8203.

出版信息

Biometrics. 1991 Dec;47(4):1489-504.

PMID:1786327
Abstract

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.

摘要

本文描述了一种用于剂量反应研究的混合模型,其中对连续变量的测量表明,一些动物不受治疗影响。该模型将动物对治疗“有反应”概率的剂量逻辑回归与有反应者均值的剂量线性回归相结合。描述了通过期望最大化(EM)算法进行的最大似然估计,并使用似然比检验来区分完整模型和有意义的简化参数版本。通过三个实际数据示例说明了该模型的使用。

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