The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
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A Targeted Maximum Likelihood Estimator for Two-Stage Designs
1University of California, Berkeley
2University of California, Berkeley
Citation Information: The International Journal of Biostatistics. Volume 7, Issue 1, Pages 1–21, ISSN (Online) 1557-4679, DOI: https://doi.org/10.2202/1557-4679.1217, March 2011
- Published Online:
We consider two-stage sampling designs, including so-called nested case control studies, where one takes a random sample from a target population and completes measurements on each subject in the first stage. The second stage involves drawing a subsample from the original sample, collecting additional data on the subsample. This data structure can be viewed as a missing data structure on the full-data structure collected in the second-stage of the study. Methods for analyzing two-stage designs include parametric maximum likelihood estimation and estimating equation methodology. We propose an inverse probability of censoring weighted targeted maximum likelihood estimator (IPCW-TMLE) in two-stage sampling designs and present simulation studies featuring this estimator.
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