Literature DB >> 17688496

Application of the principal stratification approach to the Faenza randomized experiment on breast self-examination.

A Mattei1, F Mealli.   

Abstract

In this article we present an extended framework based on the principal stratification approach (Frangakis and Rubin, 2002, Biometrics 58, 21-29), for the analysis of data from randomized experiments which suffer from treatment noncompliance, missing outcomes following treatment noncompliance, and "truncation by death." We are not aware of any previous work that addresses all these complications jointly. This framework is illustrated in the context of a randomized trial of breast self-examination.

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Year:  2007        PMID: 17688496     DOI: 10.1111/j.1541-0420.2006.00684.x

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


  5 in total

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

Authors:  Scott Schwartz; Fan Li; Jerome P Reiter
Journal:  Stat Med       Date:  2012-02-24       Impact factor: 2.373

Review 2.  Handling missing data in randomized experiments with noncompliance.

Authors:  Booil Jo; Elizabeth M Ginexi; Nicholas S Ialongo
Journal:  Prev Sci       Date:  2010-12

3.  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

4.  Sensitivity Analysis and Bounding of Causal Effects With Alternative Identifying Assumptions.

Authors:  Booil Jo; Amiram D Vinokur
Journal:  J Educ Behav Stat       Date:  2011-08

5.  Causal inference with longitudinal outcomes and non-ignorable drop-out: Estimating the effect of living alone on cognitive decline.

Authors:  Maria Josefsson; Xavier de Luna; Michael J Daniels; Lars Nyberg
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2015-06-23       Impact factor: 1.864

  5 in total

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