Computes bounds on the p-value for the treatment effect over a grid of
values of gamma (the maximum odds ratio of differential treatment
assignment due to an unobserved confounder). Uses the Wilcoxon
signed-rank approach. For exact bounds, see
sensitivitymv::senmv or the
rbounds package.
Usage
morie_matching_rosenbaum_bounds(
data,
outcome,
treatment,
match_pairs,
gamma_range = NULL
)
Arguments
- data
Data frame.
- outcome, treatment
Column names.
- match_pairs
Data frame of matched indices.
- gamma_range
Optional numeric vector of \(\Gamma\) values.
Value
A data frame with columns gamma, p_lower,
p_upper, significant_lower, significant_upper.
References
Rosenbaum, P. R. (2002). Observational Studies
(2nd ed.). Springer.
Examples
if (FALSE) { # \dontrun{
morie_matching_rosenbaum_bounds(df, "y", "d", res$match_pairs)
} # }