tehtuner 0.3.0

Adds support for classification trees in Step 2 by setting step2 = 'classtree' with a given threshold of threshold.

Adds the print.tunevt method.

tehtuner 0.2.1

Fixes a bug where zbar was calculated using the mean difference in the first column of the data instead of using the location of the variable Y.

tehtuner 0.2.0

Adds the parallel option to tunevt to support parallel backends.

tehtuner 0.1.1

This patch reconciles an invalid URI in the tunevt documentation’s references.

tehtuner 0.1.0

This is a new package that implements the Virtual Twins algorithm for subgroup identification (Foster et al., 2011) while controlling the probability of falsely detecting differential treatment effects when the conditional treatment effect is constant across the population of interest. These methods were originally presented in Wolf et al. (2022).


Key function