Run post-treatment bounds.
Usage
post_bounds(
formula,
data,
moderator,
sims = 1000,
conf_level = 0.95,
moderator_mono = NULL,
stable_mod = FALSE,
nondiff = FALSE,
progress = TRUE
)
Arguments
- formula
A formula with syntax
y ~ t
, wherey
is the (unquoted) name of the outcome andt
is the (unquoted) name of the treatment.- data
A data.frame containing variables in the formula, moderator, and covariates arguments.
- moderator
A one-sided formuala with syntax
~ d
, whered
is the (unquoted) name of the moderator variable for the CATE.- sims
An integer indicating the number of simulations for the bootstrap confidence intervals for the bounds.
- conf_level
A numeric indicating the confidence level for the bootstrap confidence intervals.
- moderator_mono
A integer or vector of length 2 indicating if the bounds should assume monotonicity of the effect of the post-test on the moderator with
1
indicating that the post-test effect is positive and-1
indicating that it is negative. The vector of length 2 allows the monotonicity assumption to vary by treatment status with the first entry being for control and the second for treated.- stable_mod
A logical value indicating if the bounds should assume that the moderator is unaffected by pre-vs-post measurement under the control condition.
- nondiff
A logical value indicating if the bounds should assume the treatment effect on the moderator is independent of the potential outcomes.
- progress
A logical indicating if progress bars should be displayed. Defaults to TRUE.
Examples
data(delponte)
post_bounds(
formula = angry_bin ~ t_commonality,
data = delponte,
moderator = ~ itaid_bin
)
#> Bootstrap running...
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#> $lower
#> [1] -1.4
#>
#> $upper
#> [1] 1.4
#>
#> $ci_lower
#> [1] -1.45455
#>
#> $ci_upper
#> [1] 1.45455
#>
#> $post_est
#> [1] -0.2701678
#>