estimate_ci_wmean {drord} R Documentation

## Compute confidence interval/s for the weight mean parameters

### Description

Compute confidence interval/s for the weight mean parameters

### Usage

estimate_ci_wmean(
out,
treat,
covar,
wmean_est,
alpha = 0.05,
out_levels = order(unique(out)),
out_form = NULL,
out_weights = rep(1, length(out_levels)),
out_model,
treat_form = "1",
ci = c("bca", "wald"),
nboot = 10000
)


### Arguments

 out A numeric vector containing the outcomes. Missing outcomes are allowed. treat A numeric vector containing treatment status. Missing values are not allowed unless the corresponding entry in out is also missing. Only values of 0 or 1 are treated as actual treatment levels. Any other value is assumed to encode a value for which the outcome is missing and the corresponding outcome value is ignored. covar A data.frame containing the covariates to include in the working proportional odds model. wmean_est The point estimates for weighted means alpha Confidence intervals have nominal level 1-alpha. out_levels A numeric vector containing all ordered levels of the outcome. out_form The right-hand side of a regression formula for the working proportional odds model. NOTE: THIS FORMULA MUST NOT SUPPRESS THE INTERCEPT. out_weights A vector of numeric weights with length equal to the length of out_levels. out_model Which R function should be used to fit the proportional odds model. Options are "polr" (from the MASS package), "vglm" (from the VGAM package), or "clm" (from the ordinal package). treat_form The right-hand side of a regression formula for the working model of treatment probability as a function of covariates ci A vector of characters indicating which confidence intervals should be computed ("bca" and/or "wald") nboot Number of bootstrap replicates used to compute bootstrap confidence intervals.

### Value

List with wald and bca-estimated confidence intervals for the weighted mean parameters.

[Package drord version 1.0.1 Index]