Abstract
We consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals is drawn from a population. On these individuals, information is obtained on treatment, outcome and a few low dimensional covariates. These individuals are then stratified according to these factors. In the second phase, a random subsample of individuals is drawn from each stratum, with known stratum-specific selection probabilities. On these individuals, a rich set of covariates is collected. In this setting, we introduce five estimators: simple inverse weighted; simple doubly robust; enriched inverse weighted; enriched doubly robust; locally efficient. We evaluate the finite sample performance of these estimators in a simulation study. We also use our methodology to estimate the causal effect of trauma care on in-hospital mortality by using data from the National Study of Cost and Outcomes of Trauma.
Original language | English (US) |
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Pages (from-to) | 947-969 |
Number of pages | 23 |
Journal | Journal of the Royal Statistical Society. Series B: Statistical Methodology |
Volume | 71 |
Issue number | 5 |
DOIs | |
State | Published - Nov 2009 |
Keywords
- Doubly robust estimator
- Outcome-dependent sampling
- Two-phase sampling
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty