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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.

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Principal Stratification and Attribution Prohibition: Good Ideas Taken Too Far

Marshall Joffe1

1University of Pennsylvania

Citation Information: The International Journal of Biostatistics. Volume 7, Issue 1, Pages 1–22, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1367, September 2011

Publication History

Published Online:
2011-09-14

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.

Keywords: principal stratification; causal inference

Citing Articles

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[1]
Ashley I. Naimi and Eric J. Tchetgen Tchetgen
American Journal of Epidemiology, 2015, Volume 181, Number 8, Page 571
[2]
X. Lu, D.V. Mehrotra, and B.E. Shepherd
Statistics in Medicine, 2013, Volume 32, Number 26, Page 4526
[3]
Michael Baiocchi, Jing Cheng, and Dylan S. Small
Statistics in Medicine, 2014, Volume 33, Number 13, Page 2297
[4]
Dustin M. Long and Michael G. Hudgens
Biometrics, 2013, Volume 69, Number 4, Page 812

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