Literature DB >> 18759834

Sensitivity analysis for principal stratum direct effects, with an application to a study of physical activity and coronary heart disease.

Arvid Sjölander1, Keith Humphreys, Stijn Vansteelandt, Rino Bellocco, Juni Palmgren.   

Abstract

SUMMARY: In many studies, the aim is to learn about the direct exposure effect, that is, the effect not mediated through an intermediate variable. For example, in circulation disease studies it may be of interest to assess whether a suitable level of physical activity can prevent disease, even if it fails to prevent obesity. It is well known that stratification on the intermediate may introduce a so-called posttreatment selection bias. To handle this problem, we use the framework of principal stratification (Frangakis and Rubin, 2002, Biometrics 58, 21-29) to define a causally relevant estimand--the principal stratum direct effect (PSDE). The PSDE is not identified in our setting. We propose a method of sensitivity analysis that yields a range of plausible values for the causal estimand. We compare our work to similar methods proposed in the literature for handling the related problem of "truncation by death."

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Year:  2009        PMID: 18759834     DOI: 10.1111/j.1541-0420.2008.01108.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  10 in total

1.  Bias formulas for sensitivity analysis for direct and indirect effects.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2010-07       Impact factor: 4.822

2.  Principal stratification--uses and limitations.

Authors:  Tyler J Vanderweele
Journal:  Int J Biostat       Date:  2011-07-11       Impact factor: 0.968

3.  Sensitivity analysis for unmeasured confounding in principal stratification settings with binary variables.

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Journal:  Stat Med       Date:  2012-02-24       Impact factor: 2.373

4.  A tutorial on principal stratification-based sensitivity analysis: application to smoking cessation studies.

Authors:  Brian L Egleston; Karen L Cropsey; Amy B Lazev; Carolyn J Heckman
Journal:  Clin Trials       Date:  2010-04-27       Impact factor: 2.486

5.  A simple method for principal strata effects when the outcome has been truncated due to death.

Authors:  Yasutaka Chiba; Tyler J VanderWeele
Journal:  Am J Epidemiol       Date:  2011-02-25       Impact factor: 4.897

6.  Conditioning on intermediates in perinatal epidemiology.

Authors:  Tyler J VanderWeele; Sunni L Mumford; Enrique F Schisterman
Journal:  Epidemiology       Date:  2012-01       Impact factor: 4.822

7.  On causal inference in the presence of interference.

Authors:  Eric J Tchetgen Tchetgen; Tyler J VanderWeele
Journal:  Stat Methods Med Res       Date:  2010-11-10       Impact factor: 3.021

8.  Rank-based principal stratum sensitivity analyses.

Authors:  X Lu; D V Mehrotra; B E Shepherd
Journal:  Stat Med       Date:  2013-05-19       Impact factor: 2.373

9.  Genetic markers as instrumental variables.

Authors:  Stephanie von Hinke; George Davey Smith; Debbie A Lawlor; Carol Propper; Frank Windmeijer
Journal:  J Health Econ       Date:  2015-11-10       Impact factor: 3.883

10.  A comparison of methods to estimate the survivor average causal effect in the presence of missing data: a simulation study.

Authors:  Myra B McGuinness; Jessica Kasza; Amalia Karahalios; Robyn H Guymer; Robert P Finger; Julie A Simpson
Journal:  BMC Med Res Methodol       Date:  2019-12-03       Impact factor: 4.615

  10 in total

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