Communication Skills in Video Games: Propensity Score Matching in R

The researchers studying how playing NERD affects communication skills knew their sample was highly unbalanced, so they thought that matching techniques may be required. With the dataset, NERD, use matching techniques to better estimate the average treatment effect of playing NERD on communication skills. Regression models alone aren't always convincing for measuring causal effects in unbalanced data (even under unconfoundedness). A more robust way to test the effect of our treatment on communication skills is through matching methods. Matching methods balance the treatment group with the control group so that they are more identical.

In R, the best tool for doing matching is the "MatchIt" package. Let's use the MatchIt package to subset our NERD dataset so that our control group contains observations that are most similar to those in our treatment group. There are many methods for matching data, but in this question, we use MatchIt's default methods.

1) Build a model for Treatment based on all of the control variables.
2) Subset our data to just the units who are likely to be in the treatment group.
3) Use matching techniques to balance the dataset.
4) Estimate standard OLS regression model for communication skills (Communication) based on all other variables in the matched dataset (match.NERD).
5) Check the statistical significance of the regression on the matched data.

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Exercise

Communication Skills in Video Games: Propensity Score Matching in R

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