Abstract
In the Chap. 23 methods for assessing confounders were reviewed. 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. This chapter assesses propensity score and propensity score matching.
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© 2016 Springer International Publishing Switzerland
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Cleophas, T.J., Zwinderman, A.H. (2016). Propensity Scores and Propensity Score Matching for Assessing Multiple Confounders. In: Clinical Data Analysis on a Pocket Calculator. Springer, Cham. https://doi.org/10.1007/978-3-319-27104-0_24
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DOI: https://doi.org/10.1007/978-3-319-27104-0_24
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27103-3
Online ISBN: 978-3-319-27104-0
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