USPS: Unsupervised and Supervised methods of Propensity Score Adjustment for Bias

Unsupervised methods: Define Local Treatment Differences (LTDs) and Local Average Outcomes (LAOs) within Clusters of well-matched patients and display their distributions across Clusters. This form of Nonparametric Preprocessing of observational data is also called Local Control because it uses post-hoc blocking to implement nested ANOVA (treatment within cluster.) Supervised methods: Estimate and Validate Propensity Scores and use them to either sub-group or smooth observed patient outcomes over the common support of alternative treatment cohorts.

Version: 1.2-1
Depends: R (≥ 1.8.0), cluster, lattice, gss
Published: 2011-12-27
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob at att.net>
License: GPL (≥ 2)
URL: http://www.r-project.org, http://members.iquest.net/~softrx/
In views: SocialSciences
CRAN checks: USPS results

Downloads:

Package source: USPS_1.2-1.tar.gz
MacOS X binary: USPS_1.2-1.tgz
Windows binary: USPS_1.2-1.zip
Reference manual: USPS.pdf
Vignettes: Unsupervised and Supervised Methods of Propensity Adjustment for Bias
Old sources: USPS archive