bca_wmean {drord}

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_wmean(
  treat,
  covar,
  out,
  nboot,
  treat_form,
  out_levels,
  out_form,
  out_weights,
  out_model,
  wmean_est,
  alpha = 0.05
)

Arguments

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.

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_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).

wmean_est

The estimated weighted means + estimated covariance matrix.

alpha

Level of confidence interval.

Value

matrix with treatment-specific weighted mean CIs and CI for difference.