estimate_ci_logodds: Compute confidence interval/s for the log-odds parameters

Description

Compute confidence interval/s for the log-odds parameters

Usage

estimate_ci_logodds(
  logodds_est,
  cdf_est,
  out_form,
  covar,
  treat_prob_est,
  treat,
  treat_form,
  out,
  ci,
  alpha = 0.05,
  nboot,
  out_levels,
  out_model,
  ...
)

Arguments

logodds_est

The point estimates for log-odds.

cdf_est

A list of treatment-specific CDF estimates.

out_form

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

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

A numeric vector containing treatment status. Should only assume a value 0 or 1.

treat_form

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

out

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

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

alpha

Confidence intervals have nominal level 1-alpha.

nboot

Number of bootstrap replicates used to compute bootstrap confidence intervals.

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).

...

Other options (not currently used).

Value

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