Instructional Videos
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This series of three training videos provides researchers and analysts with an overview of causal inference and the role of propensity scores in analysis. The videos provide step-by-step procedures for implementing propensity score analyses involving two or more treatment groups using the TWANG (Toolkit for Weighting and Analysis of Nonequivalent Groups) data analysis package.
R Tutorials
Greg Ridgeway, Daniel F. McCaffrey, Andrew R. Morral, Lane F. Burgette, Beth Ann Griffin
This tutorial describes the use of the TWANG package in R to estimate propensity score weights when there are two treatment groups, and how to use TWANG to estimate nonresponse weights. Specifically, it describes the "ps" function (which stands for Propensity Scores), the proper syntax for using the function, and the features the function contains.
Propensity Scores for Multiple Treatments: A Tutorial for the mnps Function
— 2013
Lane F. Burgette, Beth Ann Griffin, Daniel F. McCaffrey
This tutorial describes the use of the TWANG package in R to estimate propensity score weights when there are more than two treatments. Specifically, it describes the "mnps" function (which stands for Multinomial Propensity Scores), the proper syntax for using the function, and the features the function contains.
Lane F. Burgette, Beth Ann Griffin, Daniel F. McCaffrey
This tutorial describes the use of the TWANG package in R to estimate inverse probability of treatment weights (IPTWs) when one has time varying treatments or sequences of treatments over time. Specifically, it describes the "iptw" function (which stands for Inverse Probability of Treatment Weight), the proper syntax for using the function, and the features the function contains.
SAS Tutorials
Daniel F. McCaffrey,
Craig Martin,
Lane F. Burgette,
Beth Ann Griffin
This tutorial describes the use of the TWANG package in SAS to estimate propensity score weights when there are two treatment groups, and how to use TWANG to estimate nonresponse weights. Specifically, it describes the syntax and features related to the implementation of the PS function in the SAS TWANG macros. The PS function, which stands for propensity scores, estimates propensity score weights for studies involving two treatment or exposure groups. The SAS TWANG macros were developed to support the use of the TWANG tools without requiring analysts to learn R.
Daniel F. McCaffrey, Lane F. Burgette,
Beth Ann Griffin, Craig Martin
This tutorial explains the syntax and features related to the implementation of the MNPS function in the SAS TWANG macros. The MNPS function, which stands for multinomial propensity scores, estimates propensity score weights for studies involving more than two treatment or exposure groups. The SAS TWANG macros were developed to support the use of the TWANG tools without requiring analysts to learn R.
Stata Tutorials
Matthew Cefalu, Shuangshuang Liu, Craig Martin
The Stata TWANG commands were developed in 2015 to support the use of the TWANG tools without requiring researchers and analysts to learn R. This tutorial provides an introduction to TWANG and demonstrates its use through illustrative examples. This tool includes the TWANG commands for Stata, a tutorial on their use, and the sample code and datasets used in the tutorial.
Matthew Cefalu, Maya Buenaventura
This tutorial explains the syntax and features related to the implementation of the MNPS commands in the Stata TWANG series. The MNPS function, which stands for multinomial propensity scores, estimates propensity score weights for studies involving more than two treatment or exposure groups. The Stata TWANG commands were developed to support the use of the TWANG tools without requiring analysts to learn R.
