Hogan M D, Kupper L L, Most B M, Haseman J K
Am J Epidemiol. 1978 Jul;108(1):60-7.
K.J. Rothman has explored in some detail the issue of assessing the potential presence of synergism (or antagonism) in data generated from either a cohort or a case-control study. Arguing that the "natural" scale for quantifying the joint effects of two or more factors acting in combination is the probability scale, he has proposed a procedure based on a ratio-type index for evaluating two-factor interaction in the presence of non-zero background effects. In this paper, the authors review the rationale underlying Rothman's approach for a cohort study. They then present what they maintain is a simpler and more appropriate test procedure (utilizing a linear contrast of the observed risks) for the additive approximation to his basic probabilistic model of "no interaction." A likelihood ratio test based on his original model is also proposed, as well as a closed form approximation to it. Finally, the assessment of interaction in cohort studies involving exposure factors measured at more than two levels is addressed.
K.J.罗斯曼已经较为详细地探讨了在队列研究或病例对照研究产生的数据中评估协同作用(或拮抗作用)潜在存在的问题。他认为,量化两种或更多因素联合作用的“自然”尺度是概率尺度,并提出了一种基于比率型指标的程序,用于在存在非零背景效应的情况下评估双因素相互作用。在本文中,作者回顾了罗斯曼队列研究方法背后的基本原理。然后,他们提出了一种他们认为更简单、更合适的检验程序(利用观察到的风险的线性对比),用于对他的“无相互作用”基本概率模型进行相加近似。还提出了基于他原始模型的似然比检验以及对其的封闭形式近似。最后,讨论了在涉及测量水平超过两个的暴露因素的队列研究中相互作用的评估。