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.
In this tool, the authors explain the methodology behind the primary function of the selection bias decomposition (SBdecomp) package; describe its features, syntax and how to implement the function; and illustrate its use with an example.
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.
This document provides a brief tutorial on using the twangContinous package to estimate causal effects for continuous exposure variables using generalized propensity scores (GPSs) estimated via generalized boosted models (GBMs).
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.
The TWANG package has been expanded, improved, and widely distributed with funding from grant 1R01DA034065 and R01DA045049 from the National Institute on Drug Abuse.
