confint_search {crctStepdown}

Confidence interval search procedure

Description

Search for the bound of a confidence interval using permutation test statistics

Usage

confint_search(
  start,
  b,
  n,
  nmodel,
  Xnull_,
  y,
  tr_,
  new_tr_mat,
  invS,
  family,
  family2,
  Z,
  type,
  nsteps = 1000L,
  weight = TRUE,
  alpha = 0.05,
  verbose = TRUE
)

Arguments

start

Numeric value indicating the starting value for the search procedure

b

Numeric value indicating the parameter estimate

n

Integer indicating the sample size

nmodel

Integer. The number of models

Xnull_

Numeric matrix. The covariate design matrix with the treatment variable removed

y

Numeric vector of response variables

tr_

Numeric vector. The original random allocation (0s and 1s)

new_tr_mat

A matrix. Each column is a new random treatment allocation with 1s (treatment group) and 0s (control group)

invS

A matrix. If using the weighted statistic then it should be the inverse covariance matrix of the observations

family

A statsfamily object

family2

A string naming the link function

Z

Matrix. Random effects design matrix describing cluster membership

type

String. Either "rw" for Romano-Wolf, "b" or "br" for bonferroni, "h" or "hr" for Holm, or "none"

nsteps

Integer specifying the number of steps of the search procedure

weight

Logical indicating whether to use the weighted (TRUE) or unweighted (FALSE) test statistic

alpha

The function generates (1-alpha)*100% confidence intervals. Default is 0.05.

verbose

Logical indicating whether to provide detailed output.

Value

The estimated confidence interval bound