Literature DB >> 22049269

Principal stratification and attribution prohibition: good ideas taken too far.

Marshall Joffe1.   

Abstract

Pearl's article provides a useful springboard for discussing further the benefits and drawbacks of principal stratification and the associated discomfort with attributing effects to post-treatment variables. The basic insights of the approach are important: pay close attention to modification of treatment effects by variables not observable before treatment decisions are made, and be careful in attributing effects to variables when counterfactuals are ill-defined. These insights have often been taken too far in many areas of application of the approach, including instrumental variables, censoring by death, and surrogate outcomes. A novel finding is that the usual principal stratification estimand in the setting of censoring by death is by itself of little practical value in estimating intervention effects.

Entities:  

Keywords:  causal inference; principal stratification

Mesh:

Year:  2011        PMID: 22049269      PMCID: PMC3204670          DOI: 10.2202/1557-4679.1367

Source DB:  PubMed          Journal:  Int J Biostat        ISSN: 1557-4679            Impact factor:   0.968


  17 in total

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Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

2.  Sensitivity analysis for the assessment of causal vaccine effects on viral load in HIV vaccine trials.

Authors:  Peter B Gilbert; Ronald J Bosch; Michael G Hudgens
Journal:  Biometrics       Date:  2003-09       Impact factor: 2.571

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Authors:  J M Robins; S Greenland
Journal:  Epidemiology       Date:  1992-03       Impact factor: 4.822

4.  Augmented designs to assess immune response in vaccine trials.

Authors:  Dean Follmann
Journal:  Biometrics       Date:  2006-12       Impact factor: 2.571

5.  Statistical validation of intermediate endpoints for chronic diseases.

Authors:  L S Freedman; B I Graubard; A Schatzkin
Journal:  Stat Med       Date:  1992-01-30       Impact factor: 2.373

Review 6.  Principal stratification--a goal or a tool?

Authors:  Judea Pearl
Journal:  Int J Biostat       Date:  2011-03-30       Impact factor: 0.968

7.  Meta-analysis for the evaluation of potential surrogate markers.

Authors:  M J Daniels; M D Hughes
Journal:  Stat Med       Date:  1997-09-15       Impact factor: 2.373

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Authors:  J M Robins; S Greenland
Journal:  Stat Med       Date:  1989-07       Impact factor: 2.373

9.  The paired availability design: a proposal for evaluating epidural analgesia during labor.

Authors:  S G Baker; K S Lindeman
Journal:  Stat Med       Date:  1994-11-15       Impact factor: 2.373

10.  G-estimation of the effect of prophylaxis therapy for Pneumocystis carinii pneumonia on the survival of AIDS patients.

Authors:  J M Robins; D Blevins; G Ritter; M Wulfsohn
Journal:  Epidemiology       Date:  1992-07       Impact factor: 4.822

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  14 in total

1.  Nonparametric Bounds and Sensitivity Analysis of Treatment Effects.

Authors:  Amy Richardson; Michael G Hudgens; Peter B Gilbert; Jason P Fine
Journal:  Stat Sci       Date:  2014-11       Impact factor: 2.901

2.  A causal framework for classical statistical estimands in failure-time settings with competing events.

Authors:  Jessica G Young; Mats J Stensrud; Eric J Tchetgen Tchetgen; Miguel A Hernán
Journal:  Stat Med       Date:  2020-01-27       Impact factor: 2.373

3.  Invited commentary: Estimating population impact in the presence of competing events.

Authors:  Ashley I Naimi; Eric J Tchetgen Tchetgen
Journal:  Am J Epidemiol       Date:  2015-03-27       Impact factor: 4.897

4.  The challenging interpretation of instrumental variable estimates under monotonicity.

Authors:  Sonja A Swanson; Miguel A Hernán
Journal:  Int J Epidemiol       Date:  2018-08-01       Impact factor: 7.196

5.  Dealing with death when studying disease or physiological marker: the stochastic system approach to causality.

Authors:  Daniel Commenges
Journal:  Lifetime Data Anal       Date:  2018-11-17       Impact factor: 1.588

6.  Doubly robust estimation and causal inference in longitudinal studies with dropout and truncation by death.

Authors:  Michelle Shardell; Gregory E Hicks; Luigi Ferrucci
Journal:  Biostatistics       Date:  2014-07-04       Impact factor: 5.899

7.  Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.

Authors:  Peter B Gilbert; Erin E Gabriel; Ying Huang; Ivan S F Chan
Journal:  J Causal Inference       Date:  2015-02-01

8.  Designs combining instrumental variables with case-control: estimating principal strata causal effects.

Authors:  Russell T Shinohara; Constantine E Frangakis; Elizabeth Platz; Konstantinos Tsilidis
Journal:  Int J Biostat       Date:  2012-01-06       Impact factor: 0.968

9.  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

10.  Instrumental variable methods for causal inference.

Authors:  Michael Baiocchi; Jing Cheng; Dylan S Small
Journal:  Stat Med       Date:  2014-03-06       Impact factor: 2.373

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