Interactive Effects of Mixtures of Stimuli in Life Table Analysis
本文扩展了无交互作用的概率模型至生存数据，提出了用于分组时间数据的似然比统计量和标准化交互统计量，以及用于连续时间数据的类Mantel-Haenszel统计量，并通过蒙特卡洛研究考察小样本性质。
An interaction is a response to a mixture of stimuli that, based on the responses to the individual stimuli, seems unexpectedly large or small. The conclusions about the presence of interactions can depend upon the chosen parameterization. For dichotomous outcome variables, a simple probabilistic model of no interaction exists (Finney, 1952). In this model, individuals are at risk from challenges from the background and the separate stimuli, all acting independently. In this paper, this model is extended to survivorship data. To test the hypothesis of no interaction, a likelihood ratio statistic and a statistic based on a standardized interaction are proposed for grouped-time data. A statistic in the spirit of Mantel—Haenszel is constructed for continuous-time data. Asymptotic relative efficiencies of these tests versus the parametric likelihood ratio test are calculated. A limited Monte Carlo study is performed to investigate the small sample properties.