Estimation of treatment effects in randomized trials with non-compliance and a dichotomous outcome
AbstractWe propose a class of estimators of the treatment effect on a dichotomous outcome among the treated subjects within covariate and treatment arm strata in randomized trials with non-compliance. Recent papers by Vansteelandt and Goetghebeur, and Robins and Rotnitzky have presented consistent and asymptotically linear estimators of a causal odds ratio, which rely, beyond correct specification of a model for the causal odds ratio, on a correctly specified model for a potentially high dimensional nuisance parameter. In this paper we propose consistent, asymptotically linear and locally efficient estimators of a causal relative risk and a new parameter-called a switch causal relative risk-which relies only on the correct specification of a model for the parameter of interest. Our estimators are always consistent and asymptotically linear at the null hypothesis of no-treatment effect, thereby providing valid testing procedures. We examine the finite sample properties of these instrumental-variable-based estimators and the associated testing procedures in simulations and a data analysis of decaffeinated coffee consumption and miscarriage. Copyright 2007 Royal Statistical Society.
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Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series B (Statistical Methodology).
Volume (Year): 69 (2007)
Issue (Month): 3 ()
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- Paul S. Clarke; & Tom M. Palmer; & Frank Windmeijer, 2012.
"Estimating structural mean models with multiple instrumental variables using the generalised method of moments,"
Health, Econometrics and Data Group (HEDG) Working Papers
12/23, HEDG, c/o Department of Economics, University of York.
- Paul S. Clarke & Tom M. Palmer & Frank Windmeijer, 2011. "Estimating structural mean models with multiple instrumental variables using the generalised method of moments," CeMMAP working papers CWP28/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Paul S. Clarke & Tom M. Palmer & Frank Windmeijer, 2011. "Estimating Structural Mean Models with Multiple Instrumental Variables using the Generalised Method of Moments," The Centre for Market and Public Organisation 11/266, Department of Economics, University of Bristol, UK.
- Paul Clarke & Frank Windmeijer, 2009.
"Identification of Causal Effects on Binary Outcomes Using Structural Mean Models,"
The Centre for Market and Public Organisation
09/217, Department of Economics, University of Bristol, UK.
- Paul Clarke & Frank Windmeijer, 2010. "Identification of causal effects on binary outcomes using structural mean models," CeMMAP working papers CWP02/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Paul S. Clarke & Frank Windmeijer, 2012.
"Instrumental Variable Estimators for Binary Outcomes,"
Journal of the American Statistical Association,
Taylor & Francis Journals, vol. 107(500), pages 1638-1652, December.
- Paul Clarke & Frank Windmeijer, 2010. "Instrumental Variable Estimators for Binary Outcomes," The Centre for Market and Public Organisation 10/239, Department of Economics, University of Bristol, UK.
- Paul Clarke & Frank Windmeijer, 2009. "Instrumental Variable Estimators for Binary Outcomes," The Centre for Market and Public Organisation 09/209, Department of Economics, University of Bristol, UK.
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