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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.


IMPACT FACTOR 2015: 0.667
5-year IMPACT FACTOR: 1.188

SCImago Journal Rank (SJR) 2015: 0.495
Source Normalized Impact per Paper (SNIP) 2015: 0.180
Impact per Publication (IPP) 2015: 0.319

Mathematical Citation Quotient (MCQ) 2015: 0.04

Online
ISSN
1557-4679
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A Targeted Maximum Likelihood Estimator for Two-Stage Designs

Sherri Rose1 / Mark J. van der Laan2

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

Publication History

Published Online:
2011-03-11

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.

Keywords: two-stage designs; targeted maximum likelihood estimators; nested case control studies; double robust estimation

Citing Articles

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[1]
Sherri Rose, Julie Shi, Thomas G. McGuire, and Sharon-Lise T. Normand
Statistics in Biosciences, 2015
[2]
Mark J. van der Laan and Richard J. C. M. Starmans
Advances in Statistics, 2014, Volume 2014, Page 1
[3]
Paul S. Albert, Aiyi Liu, and Tonja Nansel
Biometrics, 2014, Volume 70, Number 1, Page 175

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