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Estimating Moderated Causal Effects with Time-Varying Treatments and Time-Varying Moderators: Structural Nested Mean Models and Regression with Residuals
Sociological Methodology ( IF 2.4 ) Pub Date : 2017-04-27 , DOI: 10.1177/0081175017701180
Geoffrey T Wodtke 1 , Daniel Almirall 2
Affiliation  

Individuals differ in how they respond to a particular treatment or exposure, and social scientists are often interested in understanding how treatment effects are moderated by observed characteristics of individuals. Effect moderation occurs when individual covariates dampen or amplify the effect of some exposure. This article focuses on estimating moderated causal effects in longitudinal settings in which both the treatment and effect moderator vary over time. Effect moderation is typically examined using covariate by treatment interactions in regression analyses, but in the longitudinal setting, this approach may be problematic because time-varying moderators of future treatment may be affected by prior treatment—for example, moderators may also be mediators—and naively conditioning on an outcome of treatment in a conventional regression model can lead to bias. This article introduces to sociology moderated intermediate causal effects and the structural nested mean model for analyzing effect moderation in the longitudinal setting. It discusses problems with conventional regression and presents a new approach to estimation (regression with residuals) that avoids these problems. The method is illustrated using longitudinal data from the Panel Study of Income Dynamics to examine whether the effects of time-varying exposures to poor neighborhoods on the risk for adolescent childbearing are moderated by time-varying family income.

中文翻译:

使用时变处理和时变调节因子估计调节因果效应:结构嵌套均值模型和残差回归

个体对特定治疗或暴露的反应不同,社会科学家通常有兴趣了解观察到的个体特征如何调节治疗效果。当个体协变量抑制或放大某些暴露的影响时,就会发生效应缓和。本文侧重于估计纵向设置中的缓和因果效应,其中处理和效应调节器随时间而变化。通常在回归分析中使用协变量通过治疗相互作用来检查效果调节,但在纵向设置中,这种方法可能有问题,因为未来治疗的时变调节因子可能会受到先前治疗的影响——例如,调节因子也可能是调节因子——在传统回归模型中对治疗结果进行天真的调节会导致偏差。本文介绍了社会学调节的中间因果效应和用于分析纵向环境中的效应调节的结构嵌套平均模型。它讨论了传统回归的问题,并提出了一种避免这些问题的新估计方法(残差回归)。该方法使用收入动态小组研究的纵向数据来说明,以检查随时间变化的贫困社区暴露对青少年生育风险的影响是否受到随时间变化的家庭收入的影响。本文介绍了社会学调节的中间因果效应和用于分析纵向环境中的效应调节的结构嵌套平均模型。它讨论了传统回归的问题,并提出了一种避免这些问题的新估计方法(残差回归)。该方法使用收入动态小组研究的纵向数据来说明,以检查随时间变化的贫困社区暴露对青少年生育风险的影响是否受到随时间变化的家庭收入的影响。本文介绍了社会学调节的中间因果效应和用于分析纵向环境中的效应调节的结构嵌套平均模型。它讨论了传统回归的问题,并提出了一种避免这些问题的新估计方法(残差回归)。该方法使用收入动态小组研究的纵向数据来说明,以检查随时间变化的贫困社区暴露对青少年生育风险的影响是否受到随时间变化的家庭收入的影响。
更新日期:2017-04-27
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