mcse_internal: Internal MCSE Computations

In rbmi: Reference Based Multiple Imputation

Internal MCSE Computations

Description

These functions are used by mcse() to compute the Monte Carlo standard error using the Jackknife approach.

Usage

mcse_jackknife(results, omit_index, conf.level, alternative)

jackknife_se(pars_jackknife)

mcse_combine_all_pars(jackknife_results)

Arguments

results	an analysis object created by analyse().
omit_index	the index of the result to omit.
conf.level	confidence level of the returned confidence interval. Must be a single number between 0 and 1. Default is 0.95.
alternative	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
pars_jackknife	the numeric vector of the jackknife results.
jackknife_results	the list of jackknife results of all parameters, in the same format as the pooled parameter estimates.

Value

mcse_jackknife() returns the pooled parameter estimates (in the same structure as the pars element of a pool() object) recomputed with the omit_index-th result left out.

jackknife_se() returns the numeric scalar jackknife standard error computed from pars_jackknife.

mcse_combine_all_pars() returns a list mirroring the structure of the pooled parameters in which each statistic is replaced by its jackknife Monte Carlo standard error.

rbmi documentation built on July 23, 2026, 1:08 a.m.