Causal Tools Project

January 2021 Newsletter

Shiny App for Three or More Treatments

This is a user-friendly, menu-driven Shiny application (app) that can be used to estimate propensity score weights for studies with three or more treatment groups. It also estimates the needed treatment effect estimates using those propensity score weights. The app includes a tutorial, which demonstrates use of the TWANG Shiny app through an illustrative example and toy dataset. It provides a nice complement to our binary SHINY App for Two Treatments.

Selection Bias Decomposition (SBdecomp) Tool

The SBdecomp package for R can be used to quantify the proportion of the estimated selection bias explained by each observed confounder when estimating causal effects using propensity score weights. It includes two approaches to quantify the proportion of the selection bias explained by each observed confounder—a single confounder removal approach and a single confounder inclusion approach. This tool can help analyze data where there is a substantive interest in identifying the variable or variables that explains the largest proportion of the estimated selection bias.

Causal Inference Short Course/Educational Videos

This series of eight training videos provides researchers and analysts with an overview of causal inference and the role of propensity scores in analysis. It introduces causal modeling using the potential outcomes framework and propensity score weights to estimate causal effects from observational data. Presenters demonstrate how propensity score weights can be used to estimate intervention effects, how to evaluate balance before and after propensity score weighting, and how to fit models with available software in Stata and R. Tools are also available in SAS and Shiny. Those who take the course learn how to implement propensity score weighting using state-of-the-art methods and gain insights into some of the practical issues around evaluating the quality of propensity score weights for two or more treatment groups and time-varying treatments.

R Tools

• Continuous exposures/treatment tool (twangContinuous) – This tool estimates generalized propensity score weights for continuous exposures/treatments using generalized boosted models (GBM).
• Omitted variable sensitivity analysis tool (OVtool) – This tool assesses the sensitivity of treatment effects and statistical significance to an unobserved confounder.
• Twang 2.0 – Our updated TWANG package expands the original package to include xgboost for estimation of propensity score weights with the goal of improving the performance of the TWANG package for big data.
• Entropy balancing for binary and continuous trts (entbal) – This tool estimates causal treatment effects for binary and continuous treatments using entropy balancing (EB).

R Tools

• Causal mediation tool (wgtmed) — This tool will conduct causal mediation to estimate natural direct and indirect effects for one or more mediators using a weighting approach with weight estimated by GBM or logistic regression.

Shiny Tools

• TWANG IPTW Shiny app — This user-friendly, menu-driven app estimates inverse probability of treatment weights for time-varying treatments groups using GBM.
• Covariate Balance Web App (CoBApp) — This user-friendly, menu-driven app estimates balancing weights for 9 different propensity score and entropy balancing methods, selects the optimal set of weights, performs treatment effect estimation, and helps users carefully assess the validity of both the overlap and unobserved confounding assumptions required for valid inference.

Stata Tools

• IPTW Macro — This macro will estimate inverse probability of treatment weights for time-varying treatments using GBM

Shiny Tools

• Shiny App for Two Treatments
• Shiny App for Three or More Treatments

SAS Tools

• TWANG Macro Package — This package contains commands for estimating propensity score weights for two groups (using the %ps command) and for more than two groups (using the %mnps command). It also contains a command (using the %dxwts command) for assessing the covariate balance achieved by any set of weights.

Stata Tools

• Support Files for PS and MNPS — This set of files supports estimating propensity score weights for two groups (using the ps command) and more than two groups (using the ps and mnps command) and for checking the balance of groups after weighting.

R Tools

• The twang R library on CRAN contains:
  • ps command — to estimate propensity score weights for two groups
  • mnps command — to estimate propensity score weights for more than two groups
  • iptw command — to estimate inverse probability of treatment weights for time-varying treatments.
• Selection Bias Decomposition (SBdecomp) Tool