confint_search: Confidence interval search procedure

In samuel-watson/glmmr: Design and analysis for generalised linear mixed models in R

Confidence interval search procedure

Usage

confint_search(
  start,
  b,
  Xnull_,
  y_,
  tr_,
  new_tr_mat,
  xb,
  invS,
  family,
  family2,
  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
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)
xb	A numeric vector of fitted linear predictors
invS	A matrix. If using the weighted statistic then it should be the inverse covariance matrix of the observations
family	A stats[family] object
family2	A string naming the link function
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 \item verboseLogical indicating whether to provide detailed output.

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

samuel-watson/glmmr documentation built on July 27, 2022, 10:30 p.m.