Nothing
permLLR <- function(target, dataset, xIndex, csIndex, wei = NULL, univariateModels=NULL, hash = FALSE, stat_hash=NULL, pvalue_hash=NULL,
threshold = 0.05, R = 999){
# Conditional independence test based on the Log Likelihood ratio test
if (!survival::is.Surv(target) ) stop('The survival test can not be performed without a Surv object target');
csIndex[which(is.na(csIndex))] = 0;
thres <- threshold * R + 1
if ( hash ) {
csIndex2 = csIndex[which(csIndex!=0)]
csIndex2 = sort(csIndex2)
xcs = c(xIndex, csIndex2)
key = paste(as.character(xcs) , collapse=" ");
if (is.null(stat_hash[key]) == FALSE) {
stat = stat_hash[key];
pvalue = pvalue_hash[key];
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
}
#initialization: these values will be returned whether the test cannot be carried out
pvalue <- log(1);
stat <- 0;
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
llr_results = NULL;
llr_results_full = NULL;
event <- target[,2]
#retrieving the data
x <- dataset[ , xIndex];
#if the censored indicator is empty, a dummy variable is created
numCases <- dim(dataset)[1];
if (length(event) == 0) event = vector('numeric', numCases) + 1;
if ( length(csIndex) == 0 || sum(csIndex == 0, na.rm = TRUE) > 0 ) {
llr_results <- survival::survreg( target ~ x, weights = wei, control = list(iter.max = 5000) )
stat <- 2 * abs( diff(llr_results$loglik) )
if (stat > 0) {
step <- 0
j <- 1
n <- length(x)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 <- survival::survreg( target ~ xb, weights = wei, control = list(iter.max = 5000), dist = "loglogistic" )
stat2 <- 2 * abs( diff(bit2$loglik) )
step <- step + ( stat2 > stat )
j <- j + 1
}
pvalue <- log( (step + 1) / (R + 1) )
} else pvalue <- log(1)
} else {
llr_results <- survival::survreg( target ~ ., data = as.data.frame( dataset[ , csIndex] ), weights = wei, control = list(iter.max = 5000), dist = "loglogistic" )
llr_results_full <- survival::survreg( target ~ ., data = as.data.frame( dataset[ , c(csIndex, xIndex)] ), weights = wei, control = list(iter.max = 5000), dist = "loglogistic" )
res <- anova(llr_results, llr_results_full)
stat <- abs( res[2, 6] );
if (stat > 0) {
j <- 1
step <- 0
n <- length(x)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 <- survival::survreg(target ~., data = as.data.frame( cbind(dataset[ ,csIndex], xb ) ), weights= wei, control = list(iter.max = 5000), dist = "loglogistic" )
step <- step + ( anova(llr_results, bit2)[2, 6] > stat )
j <- j + 1
}
pvalue <- (step + 1) / (R + 1)
}
}
if ( is.na(pvalue) || is.na(stat) ) {
pvalue <- log(1);
stat <- 0;
} else {
#update hash objects
if( hash ) {
stat_hash[key] <- stat; #.set(stat_hash , key , stat)
pvalue_hash[key] <- pvalue; #.set(pvalue_hash , key , pvalue)
}
}
#testerrorcaseintrycatch(4);
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
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