LocalControl: Nonparametric Methods for Generating High Quality Comparative
Effectiveness Evidence
Implements novel nonparametric approaches to address
biases and confounding when comparing treatments or exposures in
observational studies of outcomes. While designed and appropriate for use
in studies involving medicine and the life sciences, the package can be
used in other situations involving outcomes with multiple confounders.
The package implements a family of methods for non-parametric bias correction
when comparing treatments in observational studies, including survival
analysis settings, where competing risks and/or censoring may be present.
The approach extends to bias-corrected personalized predictions of treatment
outcome differences, and analysis of heterogeneity of treatment effect-sizes
across patient subgroups. For further details, please see:
Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl:
An R Package for Comparative Safety and Effectiveness Research.
Journal of Statistical Software. 2020. p. 1–32. Available from <doi:10.18637/jss.v096.i04>.
| Version: |
1.1.3 |
| Depends: |
R (≥ 3.0.0) |
| Imports: |
Rcpp, gss, cluster, lattice, stats, graphics |
| LinkingTo: |
Rcpp |
| Suggests: |
colorspace, RColorBrewer, TeachingDemos, data.table, ggplot2, gridExtra, rpart, rpart.plot, xtable |
| Published: |
2022-05-20 |
| Author: |
Nicolas R. Lauve 
[aut],
Stuart J. Nelson
[aut],
S. Stanley Young
[aut],
Robert L. Obenchain
[aut],
Melania Pintilie [ctb],
Martin Kutz [ctb],
Christophe G. Lambert
[aut, cre] |
| Maintainer: |
Christophe G. Lambert <cglambert at unm.edu> |
| License: |
Apache License 2.0 | file LICENSE |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++11 |
| Citation: |
LocalControl citation info |
| Materials: |
README NEWS |
| CRAN checks: |
LocalControl results |
Documentation:
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