Stratifying factors, like age and gender, can modify the effect of treatments and exposures on risk of a studied outcome. Several effect measures, including the relative risk, hazard ratio, odds ratio, and risk difference, can be used to measure this modification. It is known that choice of effect measure may determine the presence and direction of effect-measure modification. We show that considering the opposite outcome -- for example, recovery instead of death -- may similarly influence effect-measure modification. In fact, if the relative risk for the studied outcome and the relative risk for the opposite outcome agree about the direction of effect-measure modification, then so will the two cumulative hazard ratios, the risk difference, and the odds ratio. When risks are randomly sampled from the uniform (0,1) distribution, the probability of this happening is 5/6. Disagreement is probable enough that researchers considering one relative risk should also consider the other and further discussion if they disagree. (If possible, researchers should also report estimated risks.) We provide examples through case studies on HCV, COVID-19, and bankruptcy following melanoma treatment.

翻译：年龄和性别等分层因素可以改变治疗和接触对研究结果的风险的影响,可以使用若干效果措施来衡量这一修改,包括相对风险、危险比率、概率比和风险差异,众所周知,选择效果措施可能决定效果措施的修改的存在和方向。我们表明,考虑相反的结果 -- -- 例如,恢复而不是死亡 -- -- 也可能同样影响效果措施的修改。事实上,如果研究结果的相对风险和相反结果的相对风险就效果措施的修改方向达成一致,那么两种累积危险比率、风险差异和概率比率也将如此。当风险从制服(0,1)分布中随机抽样时,发生这种情况的概率是5/6。考虑到一个相对风险的研究人员也应考虑另一个风险的分歧是可能的,如果他们不同意的话,则应该报告估计的风险。我们通过HCV、COVID-19和梅兰诺马处理后破产的案例研究提供例子。