validate_p_reps

Check if p_reps is a valid input to tunevt

Implements methods to fit Virtual Twins models (Foster et al.
(2011) <doi:10.1002/sim.4322>) for identifying subgroups with differential
effects in the context of clinical trials while controlling the probability
of falsely detecting a differential effect when the conditional average
treatment effect is uniform across the study population using parameter
selection methods proposed in Wolf et al. (2022)
<doi:10.1177/17407745221095855>.

Jack Wolf

tehtuner

Fit and Tune Models to Detect Treatment Effect Heterogeneity

validate_p_reps function

<dl><dt>data</dt>
<dd>a data frame containing a response, binary treatment indicators,
and covariates.</dd>
<dt>p_reps</dt>
<dd>the number of permutations to run.</dd></dl>

Arguments

Check if p_reps is a valid input to tunevt — validate_p_reps

<dl>

<dt>data</dt>
<dd>a data frame containing a response, binary treatment indicators,
and covariates.</dd>


<dt>p_reps</dt>
<dd>the number of permutations to run.</dd>

</dl>

validate_p_reps: Check if p_reps is a valid input to tunevt

Description

Usage

Value

Arguments