Abstract
Propensity score are ideal for assessing confounding, particularly, if multiple confounders are in a study. E.g., age and cardiovascular risk factors may not be similarly distributed in two treatment groups of a parallel-group study. Propensity score matching is used to make observational data look like randomized controlled trial data
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Cleophas, T.J., Zwinderman, A.H. (2012). Propensity Scores and Propensity Score Matching for Assessing Multiple Confounders . In: Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2. SpringerBriefs in Statistics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4704-3_5
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DOI: https://doi.org/10.1007/978-94-007-4704-3_5
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Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4703-6
Online ISBN: 978-94-007-4704-3
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