multiPIM: Variable Importance Analysis with Population Intervention Models
Version 1.4-3

Performs variable importance analysis using a causal inference approach. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.

Getting started

Package details

AuthorStephan Ritter <>, Alan Hubbard <>, Nicholas Jewell <>
Date of publication2015-02-25 08:12:42
MaintainerStephan Ritter <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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multiPIM documentation built on May 29, 2017, 10:57 a.m.