estimate_ci_marg_dist: Compute confidence interval/s for the treatment specific PMF and CDF.

Description

Compute confidence interval/s for the treatment specific PMF and CDF.

Usage

estimate_ci_marg_dist(
  marg_cdf_est,
  marg_pmf_est,
  cdf_est,
  pmf_est,
  covar,
  treat_prob_est,
  treat_form,
  out_form,
  treat,
  ci,
  out_levels,
  out_model,
  out,
  alpha,
  nboot
)

Arguments

marg_cdf_est

Point estimate of treatment-specific CDF.

marg_pmf_est

Point estimate of treatment-specific PMF.

cdf_est

Estimates of treatment-specific conditional CDF.

pmf_est

Estimates of treatment-specific conditional PMF.

covar

A data.frame containing the covariates to include in the working proportional odds model.

treat_prob_est

Estimated probability of treatments, output from call to estimate_treat_prob.

treat_form

The right-hand side of a regression formula for the working model of treatment probability as a function of covariates

out_form

The right-hand side of a regression formula for the working proportional odds model. NOTE: THIS FORMULA MUST NOT SUPPRESS THE INTERCEPT.

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.

A vector of characters indicating which confidence intervals should be computed ("bca" and/or "wald")

out_levels

A numeric vector containing all ordered levels of the outcome.

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).

out

A numeric vector containing the outcomes. Missing outcomes are allowed.

alpha

Confidence intervals have nominal level 1-alpha.

nboot

Number of bootstrap replicates used to compute bootstrap confidence intervals.

Value

List of lists (cdf and pmf) with wald and bca-estimated confidence intervals for the marginal treatment-specific distribution functions.