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ipw: An R Package for Inverse Probability Weighting

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  • Willem M. van der Wal
  • Ronald B. Geskus
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    Abstract

    We describe the R package ipw for estimating inverse probability weights. We show how to use the package to fit marginal structural models through inverse probability weighting, to estimate causal effects. Our package can be used with data from a point treatment situation as well as with a time-varying exposure and time-varying confounders. It can be used with binomial, categorical, ordinal and continuous exposure variables.

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    File URL: http://www.jstatsoft.org/v43/i13/paper
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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 43 ()
    Issue (Month): i13 ()
    Pages:

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    Handle: RePEc:jss:jstsof:43:i13

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    Web page: http://www.jstatsoft.org/

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    Cited by:
    1. Bartolucci, Francesco & Grilli, Leonardo & Pieroni, Luca, 2012. "Estimating dynamic causal effects with unobserved confounders: a latent class version of the inverse probability weighted estimator," MPRA Paper 43430, University Library of Munich, Germany.

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