#' Calculation of all admissable z-vectors with corresponding t-statistics at least as large as the observed value of t.
#'
#' This function performs the calculation of all admissable z-vectors with corresponding t-statistics at least as large as the observed value of t for exact clustered logistic regression.
#' @param zadmis The matrix of admissable vectors.
#' @param nvec The vector of numbers of observations per cluster.
#' @param z The vector of observed z-values.
#' @param x A vector of predictor values for each cluster.
#' @keywords Exact Clustered Logistic Regression
#' @export
#' @examples
#' extremez()
extremez=function(zadmis,nvec,z,x){
ncols = dim(zadmis)[2]
tobs = tcalc(z,x)
#initialize answer to include observed values
zextreme = z
for(i in 1:ncols) #run through all admissable vectors
{
zcurrent = zadmis[,i]
tcurrent = tcalc(zcurrent,x)
if(tcurrent >= tobs)
{
zextreme = cbind(zextreme,zcurrent)
}
} #end for
#remove first column; observed z-values are recorded twice
zextremefinal = zextreme[,2:dim(zextreme)[2]]
zextremefinal
} # end extremez function
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