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multiPIM: Variable Importance Analysis with Population Intervention Models
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
Browse package contents
Package details |
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| Author | Stephan Ritter <sritter@berkeley.edu>, Alan Hubbard <hubbard@berkeley.edu>, Nicholas Jewell <jewell@berkeley.edu> |
| Maintainer | Stephan Ritter <stephanritterRpacks@gmail.com> |
| License | GPL (>= 2) |
| Version | 1.4-3 |
| URL | http://www.jstatsoft.org/v57/i08/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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