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Targeted maximum likelihood estimation in safety analysis.
- Source :
-
Journal of Clinical Epidemiology . 2013, Vol. 66 Issue 8S, pS91-S98. 8p. - Publication Year :
- 2013
-
Abstract
- Objectives: To compare the performance of a targeted maximum likelihood estimator (TMLE) and a collaborative TMLE (CTMLE) to other estimators in a drug safety analysis, including a regression-based estimator, propensity score (PS)ebased estimators, and an alternate doubly robust (DR) estimator in a real example and simulations. Study Design and Setting: The real data set is a subset of observational data from Kaiser Permanente Northern California formatted for use in active drug safety surveillance. Both the real and simulated data sets include potential confounders, a treatment variable indicating use of one of two antidiabetic treatments and an outcome variable indicating occurrence of an acute myocardial infarction (AMI). Results: In the real data example, there is no difference in AMI rates between treatments. In simulations, the double robustness property is demonstrated: DR estimators are consistent if either the initial outcome regression or PS estimator is consistent, whereas other estimators are inconsistent if the initial estimator is not consistent. In simulations with near-positivity violations, CTMLE performs well relative to other estimators by adaptively estimating the PS. Conclusion: Each of the DR estimators was consistent, and TMLE and CTMLE had the smallest mean squared error in simulations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08954356
- Volume :
- 66
- Issue :
- 8S
- Database :
- Academic Search Index
- Journal :
- Journal of Clinical Epidemiology
- Publication Type :
- Academic Journal
- Accession number :
- 89370437
- Full Text :
- https://doi.org/10.1016/j.jclinepi.2013.02.017