multiPIM (1.4-3)

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Variable Importance Analysis with Population Intervention Models.

http://www.jstatsoft.org/v57/i08/
http://cran.r-project.org/web/packages/multiPIM

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.

Maintainer: Stephan Ritter
Author(s): Stephan Ritter <sritter@berkeley.edu>, Alan Hubbard <hubbard@berkeley.edu>, Nicholas Jewell <jewell@berkeley.edu>

License: GPL (>= 2)

Uses: Does not use any package

Released about 4 years ago.


6 previous versions

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