bca_marg_dist: Compute a BCa bootstrap confidence interval for the weighted...

In drord: Doubly-Robust Estimators for Ordinal Outcomes

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_marg_dist(
  treat,
  covar,
  out,
  nboot,
  treat_form,
  out_levels,
  out_form,
  out_model,
  marg_cdf_est,
  marg_pmf_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).
marg_cdf_est	Point estimate of treatment-specific CDF.
marg_pmf_est	Point estimate of treatment-specific PMF.
alpha	Level of confidence interval.

Value

List (cdf, pmf) of lists (treat=1, treat=0) of confidence intervals for distributions.

drord documentation built on May 21, 2021, 1:06 a.m.