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A comparison of balancing scores for estimating rate ratios of count data in observational studies
Authors:Chunhao Tu  Woon Yuen Koh
Affiliation:1. College of Pharmacy, University of New England, Portland, Maine, USA;2. Department of Mathematical Sciences, University of New England, Biddeford, Maine, USA
Abstract:In this article, we conduct a Monte Carlo study to examine four balancing scores (BS1: propensity score, BS2: prognostic score, BS3: adjusted propensity score estimated by the estimated prognostic score, and BS4: adjusted propensity score estimated by the estimated prognostic score and other covariates) for adjusting bias in estimating the marginal and the conditional rate ratios of count data in observational studies. Simulation results show that BS1–BS4 are not much different in terms of estimating the marginal and the conditional rate ratios, however, choosing the appropriate matching algorithm is more important than selecting a balancing scores.
Keywords:Count data  Matching  Observational studies  Prognostic score  Propensity score
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