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ipw: An R Package for Inverse Probability Weighting [PDF]
Journal of Statistical Software, 2011 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.
Ronald B. Geskus, Willem M. van der Wal
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Accounting for nonmonotone missing data using inverse probability weighting. [PDF]
Stat Med, 2023 Inverse probability weighting can be used to correct for missing data. New estimators for the weights in the nonmonotone setting were introduced in 2018.
Ross RK +5 more
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Combining Multiple Imputation and Inverse‐Probability Weighting [PDF]
Biometrics, 2011 Summary Two approaches commonly used to deal with missing data are multiple imputation (MI) and inverse‐probability weighting (IPW). IPW is also used to adjust for unequal sampling fractions. MI is generally more efficient than IPW but more complex. Whereas IPW requires only a model for the probability that an individual has complete data (a univariate
Seaman, Shaun R. +3 more
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Robust Inference Using Inverse Probability Weighting [PDF]
Journal of the American Statistical Association, 2019 Inverse probability weighting (IPW) is widely used in empirical work in economics and other disciplines. As Gaussian approximations perform poorly in the presence of “small denominators,” trimming is routinely employed as a regularization strategy. However, ad hoc trimming of the observations renders usual inference procedures invalid for the target ...
Ma, Xinwei, Wang, Jingshen
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Application of inverse probability weights in survival analysis [PDF]
Journal of Nuclear Cardiology, 2015 Suppose that a researcher is interested in comparing two ‘‘treatments’’—A and B—and how the treatment affects an outcome of interest. The ideal study design would be to conduct a randomized trial where treatment assignment is randomly assigned. The random treatment assignment aims to make the subjects between the two treatments similar, i.e., it aims ...
Guoqiao, Wang, Inmaculada, Aban
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International Journal of Infectious Diseases, 2022 Objectives: To evaluate the effectiveness of remdesivir in the early stage of nonsevere COVID-19. Although several randomized controlled trials have compared the effectiveness of remdesivir with that of a placebo, there is limited evidence regarding its ...
Shinya Tsuzuki +20 more
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Inverse probability weighting with error-prone covariates [PDF]
Biometrika, 2013 Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which
Daniel F. McCaffrey +2 more
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PLoS ONE, 2022 Objectives While corticosteroids have been hypothesized to exert protective benefits in patients infected with SARS-CoV-2, data remain mixed. This study sought to investigate the outcomes of methylprednisone administration in an Italian cohort of ...
Lorenzo Porta +6 more
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An introduction to inverse probability of treatment weighting in observational research [PDF]
Clinical Kidney Journal, 2021 ABSTRACTIn this article we introduce the concept of inverse probability of treatment weighting (IPTW) and describe how this method can be applied to adjust for measured confounding in observational research, illustrated by a clinical example from nephrology. IPTW involves two main steps. First, the probability—or propensity—of being exposed to the risk
Chesnaye, Nicholas C +6 more
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Journal of Biostatistics and Epidemiology, 2020 Introduction: Missing values are frequently seen in data sets of research studiesespecially in medical studies.Therefore, it is essential that the data, especially in medical research should evaluate in terms of the structure of missingness.This study ...
Freshteh Osmani, Ebrahim Hajizadeh
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