ipw_acic2022

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Introductory Workshop for Using Propensity Score Weights When Drawing Causal Inferences

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# ipw_acic2022
Introductory Workshop for Using Propensity Score Weights When Drawing Causal Inferences

## Goals

To increase your understanding of:

* How to define and estimate causal effects
  * How to use propensity scores when estimating causal effects
  * How to assess the validity of key assumptions

To provide step-by-step instructions for using propensity score weights for binary treatment settings

## Schedule

Approximate Schedule

* 1:00 - 2:00 PM : Introduction to propensity scores
  * 2:00 - 2:05 PM : Break
  * 2:05 - 3:05 PM : Propensity Score Estimation Techniques
  * 3:05 - 3:10 PM : Break
  * 3:10 - 4:00 PM : Additional topics
  
## Slide location

[Slides are here](https://www.dropbox.com/sh/hc8u9e2al6yb7pv/AACcBERJDP4UBGKKlSnzgMCFa?dl=0)

## Packages you may want to explore

* `library(twang)` - Toolkit for the weighting and analysis on nonequivalent groups
  * `library(CBPS)` - Covariate Balancing Propensity Score
  * `library(ebal)` - Hainmeuller's Entropy Balancing Package
  * `library(entbal)` - Vegetabile's Entropy Balancing Package
  * `library(survey)` - Survey package for weighted outcome estimation with correct standard errors
  * `library(cobalt)` - [Covariate Balance Tables and Plots](https://ngreifer.github.io/cobalt/articles/cobalt.html)
  * `library(viridis)` - Useful Color Palette
  * `library(OVtool)` - Sensitivity Analysis for `twang`

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