Identifiability and Estimation of Causal Effects by Principal Stratification With Outcomes Truncated by Death

2011 ◽  
Vol 106 (496) ◽  
pp. 1578-1591 ◽  
Author(s):  
Peng Ding ◽  
Zhi Geng ◽  
Wei Yan ◽  
Xiao-Hua Zhou
2003 ◽  
Vol 28 (4) ◽  
pp. 353-368 ◽  
Author(s):  
Junni L. Zhang ◽  
Donald B. Rubin

The topic of “truncation by death” in randomized experiments arises in many fields, such as medicine, economics and education. Traditional approaches addressing this issue ignore the fact that the outcome after the truncation is neither “censored” nor “missing,” but should be treated as being defined on an extended sample space. Using an educational example to illustrate, we will outline here a formulation for tackling this issue, where we call the outcome “truncated by death” because there is no hidden value of the outcome variable masked by the truncating event. We first formulate the principal stratification ( Frangakis & Rubin, 2002 ) approach, and we then derive large sample bounds for causal effects within the principal strata, with or without various identification assumptions. Extensions are then briefly discussed.


2021 ◽  
Author(s):  
Moritz Marbach

Social scientists have long been interested in the persistent effects of history on contemporary behavior and attitudes. To estimate legacy effects, studies typically compare people living in places that were historically exposed to some event and those that were not. Using principal stratification, we provide a formal framework to analyze how migration limits our ability to learn about the persistent effects of history from observed differences between historically exposed and unexposed places. We state the necessary assumptions about movement behavior to causally identify legacy effects. We highlight that these assumptions are strong; therefore, we recommend that legacy studies circumvent bias by collecting data on people's place of residence at the exposure time. Reexamining a study on the persistent effects of US civil-rights protests, we show that observed attitudinal differences between residents and non-residents of historic protest sites are more likely due to migration rather than attitudinal change.


Biostatistics ◽  
2007 ◽  
Vol 9 (2) ◽  
pp. 277-289 ◽  
Author(s):  
Jason Roy ◽  
Joseph W. Hogan ◽  
Bess H. Marcus

Abstract In behavioral medicine trials, such as smoking cessation trials, 2 or more active treatments are often compared. Noncompliance by some subjects with their assigned treatment poses a challenge to the data analyst. The principal stratification framework permits inference about causal effects among subpopulations characterized by potential compliance. However, in the absence of prior information, there are 2 significant limitations: (1) the causal effects cannot be point identified for some strata and (2) individuals in the subpopulations (strata) cannot be identified. We propose to use additional information—compliance-predictive covariates—to help identify the causal effects and to help describe characteristics of the subpopulations. The probability of membership in each principal stratum is modeled as a function of these covariates. The model is constructed using marginal compliance models (which are identified) and a sensitivity parameter that captures the association between the 2 marginal distributions. We illustrate our methods in both a simulation study and an analysis of data from a smoking cessation trial.


2020 ◽  
Author(s):  
Christopher Greenwood ◽  
George Joseph Youssef ◽  
Primrose Letcher ◽  
Elizabeth Spry ◽  
Lauryn Hagg ◽  
...  

Aims: To explore the process of applying counterfactual thinking in examining causal predictors of substance use trajectories in observational cohort data. Specifically, we examine the extent to which quality of the parent-adolescent relationship and affiliations with deviant peers are causally related to trajectories of alcohol, tobacco, and cannabis use across adolescence and into young adulthood. Methods: Data were drawn from the Australian Temperament Project, a population-based cohort study that has followed a sample of young Australians from infancy to adulthood since 1983. Parent-adolescent relationship quality and deviant peer affiliations were assessed at age 13-14 years. Latent curve models were fitted for past month alcohol, tobacco, and cannabis use (n = 1,590) from age 15-16 to 27-28 years (5 waves). Confounding factors were selected in line with the counterfactual framework. Results: Following confounder adjustment, higher quality parent-adolescent relationships were associated with lower baseline cannabis use, but not alcohol or tobacco use trajectories. In contrast, affiliations with deviant peers were associated with higher baseline binge drinking, tobacco, and cannabis use, and an earlier peak in the cannabis use trajectory. Conclusions: Confounding adjustments weakened several estimated associations and the interpretation of such associations as causal is not without limitations. Nevertheless, findings suggested causal effects of both parent-adolescent relationships and deviant peer affiliations on the trajectory of substance use. Causal effects were however more pervasive (i.e., more substance types) and protracted for deviant peer affiliations. The current study encourages the exploration of causal relationships in observational cohort data, when relevant limitations are transparently acknowledged.


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