Targeted maximum likelihood estimation in safety analysis.
J Clin Epidemiol
; 66(8 Suppl): S91-8, 2013 Aug.
Article
in En
| MEDLINE
| ID: mdl-23849159
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)-based estimators, and an alternate doubly robust (DR) estimator in a real example and simulations. STUDY DESIGN ANDSETTING:
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.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Product Surveillance, Postmarketing
/
Likelihood Functions
/
Causality
/
Models, Statistical
/
Hypoglycemic Agents
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
J Clin Epidemiol
Journal subject:
EPIDEMIOLOGIA
Year:
2013
Document type:
Article
Affiliation country:
United States