Literature DB >> 18510650

A comparison of methods for estimating the causal effect of a treatment in randomized clinical trials subject to noncompliance.

Roderick J Little1, Qi Long, Xihong Lin.   

Abstract

SUMMARY: We consider the analysis of clinical trials that involve randomization to an active treatment (T = 1) or a control treatment (T = 0), when the active treatment is subject to all-or-nothing compliance. We compare three approaches to estimating treatment efficacy in this situation: as-treated analysis, per-protocol analysis, and instrumental variable (IV) estimation, where the treatment effect is estimated using the randomization indicator as an IV. Both model- and method-of-moment based IV estimators are considered. The assumptions underlying these estimators are assessed, standard errors and mean squared errors of the estimates are compared, and design implications of the three methods are examined. Extensions of the methods to include observed covariates are then discussed, emphasizing the role of compliance propensity methods and the contrasting role of covariates in these extensions. Methods are illustrated on data from the Women Take Pride study, an assessment of behavioral treatments for women with heart disease.

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Year:  2008        PMID: 18510650     DOI: 10.1111/j.1541-0420.2008.01066.x

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


  35 in total

1.  Estimating Causal Effects in Trials Involving Multi-Treatment Arms Subject to Non-compliance: A Bayesian framework.

Authors:  Qi Long; Roderick J A Little; Xihong Lin
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2010-05       Impact factor: 1.864

2.  A note about the identifiability of causal effect estimates in randomized trials with non-compliance.

Authors:  Kwun Chuen Gary Chan
Journal:  Stat Methodol       Date:  2014-01-01

3.  Principal stratification--uses and limitations.

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

4.  Causal inference in randomized clinical trials.

Authors:  Cheng Zheng; Ran Dai; Robert Peter Gale; Mei-Jie Zhang
Journal:  Bone Marrow Transplant       Date:  2019-03-26       Impact factor: 5.483

5.  Randomization-Based Inference within Principal Strata.

Authors:  Tracy L Nolen; Michael G Hudgens
Journal:  J Am Stat Assoc       Date:  2011-06       Impact factor: 5.033

6.  The Impact of Population-Based Disease Management Services on Health Care Utilisation and Costs: Results of the CAPICHe Trial.

Authors:  Paul A Scuffham; Joshua M Byrnes; Christine Pollicino; David Cross; Stan Goldstein; Shu-Kay Ng
Journal:  J Gen Intern Med       Date:  2018-09-27       Impact factor: 5.128

7.  Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

Authors:  Sam Vuchinich; Brian R Flay; Lawrence Aber; Leonard Bickman
Journal:  Prev Sci       Date:  2012-06

8.  Randomized Trial of Low-Nicotine Cigarettes and Transdermal Nicotine.

Authors:  Tracy T Smith; Joseph S Koopmeiners; Katelyn M Tessier; Esa M Davis; Cynthia A Conklin; Rachel L Denlinger-Apte; Tonya Lane; Sharon E Murphy; Jennifer W Tidey; Dorothy K Hatsukami; Eric C Donny
Journal:  Am J Prev Med       Date:  2019-10       Impact factor: 5.043

9.  The Comparative Effectiveness of Diabetes Prevention Strategies to Reduce Postpartum Weight Retention in Women With Gestational Diabetes Mellitus: The Gestational Diabetes' Effects on Moms (GEM) Cluster Randomized Controlled Trial.

Authors:  Assiamira Ferrara; Monique M Hedderson; Susan D Brown; Cheryl L Albright; Samantha F Ehrlich; Ai-Lin Tsai; Bette J Caan; Barbara Sternfeld; Nancy P Gordon; Julie A Schmittdiel; Erica P Gunderson; Ashley A Mevi; William H Herman; Jenny Ching; Yvonne Crites; Charles P Quesenberry
Journal:  Diabetes Care       Date:  2015-12-09       Impact factor: 19.112

10.  A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials.

Authors:  John Simes; Merryn Voysey; Rachel O'Connell; Paul Glasziou; James D Best; Russell Scott; Christopher Pardy; Karen Byth; David R Sullivan; Christian Ehnholm; Anthony Keech
Journal:  PLoS One       Date:  2010-01-08       Impact factor: 3.240

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