CrossSelection2years.Lasso.R

In htx-r/RiskModelNMApredictions:

#######################################################################################################
###          Selects variables via LASSO based on half RCTs ################################
###       with 100 cross validations (100 different half-datasets)###########################
#############            2 YEARS RELAPSES           ###################################
################################################################################################################


  
  library(glmnet)
  library(Hmisc)
  ####################random half RCTs from studies###############################
  for (i in 1:100) {
    Advance<-dataset[which(dataset$STUDYID=="105MS301"),]
    Advance.risk<-Advance[sample(nrow(Advance), nrow(Advance)/2),]
    todrop<-c("STUDYID","USUBJID","RELAPSE1year")
    Advance.risk<-Advance.risk[ , !(names(Advance.risk) %in% todrop)]
    
    Define<-dataset[which(dataset$STUDYID=="109MS301"),]
    Define.risk<-Define[sample(nrow(Define), nrow(Define)/2),]
    Define.risk<-Define.risk[ , !(names(Define.risk) %in% todrop)]
    
    Confirm<-dataset[which(dataset$STUDYID=="C-1801"),]
    Confirm.risk<-Confirm[sample(nrow(Confirm), nrow(Confirm)/2),]
    Confirm.risk<-Confirm.risk[ , !(names(Confirm.risk) %in% todrop)]
    
    Affirm<-dataset[which(dataset$STUDYID=="C-1802"),]
    Affirm.risk<-Affirm[sample(nrow(Affirm), nrow(Affirm)/2),]
    Affirm.risk<-Affirm.risk[ , !(names(Affirm.risk) %in% todrop)]
    
    Mscrg<-dataset[which(dataset$STUDYID=="NS26321"),]
    Mscrg.risk<-Mscrg[sample(nrow(Mscrg), nrow(Mscrg)/2),]
    Mscrg.risk<-Mscrg.risk[ , !(names(Mscrg.risk) %in% todrop)]
    ##all half studies together
    mrg<-rbind(Advance.risk,Define.risk,Confirm.risk,Affirm.risk,Mscrg.risk)
    #####################LASSO preparation####################
    
    ###blinded to treatment so drop variable TRT01A
    todrop<-c("TRT01A")
    mrg.both<-mrg[ , !(names(mrg) %in% todrop)]
    ### delete NA values (LASSO requierement)
    mrg.both<-na.omit(mrg.both)
    #### model matrix needed for LASSO
    half.matrix<-model.matrix(mrg.both$RELAPSE2year~.,data=mrg.both)
    half.matrix<-na.omit(half.matrix)
    #################################LASSO################################
    ######################################################################
    ##10 cross validations
    cv.fit.half<-cv.glmnet(x=half.matrix,y=mrg.both$RELAPSE2year,family="binomial")
    ### LASSO coefficients
    cv.coef.half<-coef(cv.fit.half,s="lambda.1se")
    ####RESULTS
    ### non zero coefficients lead to selected variables
    cv.pf.em.half<-rownames(cv.coef.half)[as.numeric(cv.coef.half)!=0]
    
    print(cv.pf.em.half)
    
  }