bca_logodds {drord} R Documentation

Compute a BCa bootstrap confidence interval for the weighted mean. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf

Description

Compute a BCa bootstrap confidence interval for the weighted mean. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf

Usage

bca_logodds(
treat,
covar,
out,
nboot,
treat_form,
out_levels,
out_form,
out_model,
logodds_est,
alpha = 0.05
)


Arguments

 treat A numeric vector containing treatment status. Should only assume a value 0 or 1. covar A data.frame containing the covariates to include in the working proportional odds model. out A numeric vector containing the outcomes. Missing outcomes are allowed. nboot Number of bootstrap replicates used to compute bootstrap confidence intervals. treat_form The right-hand side of a regression formula for the working model of treatment probability as a function of covariates 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_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). logodds_est The estimated log-odds. alpha Level of confidence interval.

Value

matrix with treatment-specific log-odds CIs and CI for difference.

[Package drord version 1.0.1 Index]