A comparison of balancing scores for estimating rate ratios of count data in observational studies |
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Authors: | Chunhao Tu Woon Yuen Koh |
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Affiliation: | 1. College of Pharmacy, University of New England, Portland, Maine, USA;2. Department of Mathematical Sciences, University of New England, Biddeford, Maine, USA |
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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. |
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Keywords: | Count data Matching Observational studies Prognostic score Propensity score |
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