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Welcome to the User Manual for hetviz, an R package designed to facilitate exploratory, hypothesis-generating analyses of treatment effect heterogeneity (TEH).

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We mean (average) treatment effect in the causal sense, as a comparison of what an outcome would have potentially been under treatment & what the outcome would have potentially been under no treatment.

• Note that this software assumes a binary treatment.

In a population, there may be subpopulations for whom their (average) treatment effect is systematically different. We refer to this systematic variability as TEH. It would be of great use to be able to empirically characterize these subpopulations in the following ways:

1. estimation of the true number of underlying subgroups
2. identification of which covariates and what values determine subpopulation membership
3. estimation of the subpopulation average treatment effect

This software allows analysts to interact with their data in ways that will allow TEH to reveal itself.