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Efficient influence curve

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Full-Text Articles in Physical Sciences and Mathematics

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan Dec 2013

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

Wenjing Zheng

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …


Adaptive Matching In Randomized Trials And Observational Studies, Mark J. Van Der Laan, Laura Balzer, Maya L. Petersen Nov 2012

Adaptive Matching In Randomized Trials And Observational Studies, Mark J. Van Der Laan, Laura Balzer, Maya L. Petersen

Laura B. Balzer

In many randomized and observational studies the allocation of treatment among a sample of n independent and identically distributed units is a function of the covariates of all sampled units. As a result, the treatment labels among the units are possibly dependent, complicating estimation and posing challenges for statistical inference. For example, cluster randomized trials frequently sample communities from some target population, construct matched pairs of communities from those included in the sample based on some metric of similarity in baseline community characteristics, and then randomly allocate a treatment and a control intervention within each matched pair. In this case, …


Why Match In Individually And Cluster Randomized Trials?, Laura B. Balzer, Maya L. Petersen, Mark J. Van Der Laan May 2012

Why Match In Individually And Cluster Randomized Trials?, Laura B. Balzer, Maya L. Petersen, Mark J. Van Der Laan

Laura B. Balzer

The decision to match individuals or clusters in randomized trials is motivated by both practical and statistical concerns. Matching protects against chance imbalances in baseline covariate distributions and is thought to improve study credibility. Matching is also implemented to increase study power. This article compares the asymptotic efficiency of the pair-matched design, where units are matched on baseline covariates and the treatment randomized within pairs, to the independent design, where units are randomly paired and the treatment randomized within pairs. We focus on estimating the average treatment effect and use the efficient influence curve to understand the information provided by …