Citation

Ross ME, Kreider AR, Huang YS, Matone M, Rubin DM, Localio AR. Am. J. Epidemiol. 2015; 181(12): 989-995.

Copyright

(Copyright © 2015, Oxford University Press)

DOI

10.1093/aje/kwu469

PMID

25995287

Abstract

Randomized controlled trials are the "gold standard" for estimating the causal effects of treatments. However, it is often not feasible to conduct such a trial because of ethical concerns or budgetary constraints. We expand upon an approach to the analysis of observational data sets that mimics a sequence of randomized studies by implementing propensity score models within each trial to achieve covariate balance, using weighting and matching. The methods are illustrated using data from a safety study of the relationship between second-generation antipsychotics and type 2 diabetes (outcome) in Medicaid-insured children aged 10-18 years across the United States from 2003 to 2007. Challenges in this data set include a rare outcome, a rare exposure, substantial and important differences between exposure groups, and a very large sample size.

Language: en