Volume 7 (2011)
Volume 5 (2009)
Volume 4 (2008)
Volume 3 (2007)
Volume 2 (2006)
Volume 1 (2005)
Most Downloaded Articles
- An Introduction to Causal Inference by Pearl, Judea
- Meta-Analysis of Observational Studies with Unmeasured Confounders by McCandless, Lawrence C.
- Accuracy of Conventional and Marginal Structural Cox Model Estimators: A Simulation Study by Xiao, Yongling/ Abrahamowicz, Michal and Moodie, Erica E. M.
- Evaluating treatment effectiveness in patient subgroups: a comparison of propensity score methods with an automated matching approach by Radice, Rosalba/ Ramsahai, Roland/ Grieve, Richard/ Kreif, Noemi/ Sadique, Zia and Sekhon, Jasjeet S.
- Special Issue on Causal Inference in Health Research by Moodie, Erica E. M./ Kaufman, Jay S. and Platt, Robert W.
Semiparametrically Efficient Estimation of Conditional Instrumental Variables Parameters
1University of California, Berkeley
Citation Information: The International Journal of Biostatistics. Volume 5, Issue 1, Pages –, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1153, June 2009
- Published Online:
In this paper, I propose a set of parameters designed to identify the slope of structural relationships based on a combination of conditioning on covariates and the use of an exogenous instrument. After giving structural interpretations to these parameters in the context of specific semiparametric models, I derive their efficient influence curves in a fully nonparametric context as well as under imposition of restrictions on the instrument. These influence curves give the semiparametric efficiency bounds for regular asymptotically linear estimators of the parameters and allow the construction of asymptotically efficient estimators. Monte Carlo experiments finally demonstrate the good finite sample performance of such estimators.