R/censIndCR.R

In MXM: Feature Selection (Including Multiple Solutions) and Bayesian Networks

censIndCR <- function(target, dataset, xIndex, csIndex, wei = NULL, univariateModels = NULL, hash = FALSE, 
                     stat_hash = NULL, pvalue_hash = NULL) {
  # 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;
  
  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);
  cox_results <- NULL;
  cox_results_full <- NULL;
  #timeIndex <- dim(dataset)[2];
  event <- target[,2]
  numCases <- dim(dataset)[1];
  oop <- options(warn = -1) 
  on.exit( options(oop) )
  if ( length(event) == 0 )   event = vector('numeric', numCases) + 1;
      if ( length(csIndex) == 0 || sum(csIndex == 0, na.rm = TRUE) > 0 ) {
        cox_results <- try( survival::coxph(target ~ dataset[, xIndex], weights = wei ), silent = TRUE )
        if ( identical( class(cox_results), "try-error" ) ) {
          stat <- NA
        } else {  
          res <- anova(cox_results)
          dof <- res[2, 3]
          stat <- res[2, 2]
          pvalue <- pchisq(stat, dof, lower.tail = FALSE, log.p = TRUE);
        }  
      } else {
        cox_results <- try( survival::coxph(target ~ ., data = as.data.frame(  dataset[ , csIndex] ), weights = wei), silent = TRUE ) 
        cox_results_full <- try( survival::coxph(target ~ ., data = as.data.frame(  dataset[ , c(csIndex, xIndex)] ), weights = wei), silent = TRUE)
        if ( identical( class(cox_results), "try-error" )  |  identical( class(cox_results_full), "try-error" ) ) {
         stat <- NA
        } else { 
          res <- anova(cox_results_full, cox_results)
          stat <- res[2, 2]
          dof <- res[2, 3]
        }
        pvalue <- pchisq(stat, dof, lower.tail = FALSE, log.p = TRUE)
      }  
      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)
        }
      }
      results <- list(pvalue = pvalue, stat = stat,  stat_hash=stat_hash, pvalue_hash=pvalue_hash);
      return(results);
}