#Dennis Moskov, Master Thesis
#standardize data base

#check classes of predictors
sapply(DB,class)

#standardize only numerical input variables
#add columns accordingly to scalevar and DBs
scalevar<-setdiff(names(DB),c("prep.meth","article","X.MeOH","S.MeOH","Y.MeOH"))  
DBs<-data.frame(sapply(DB[,scalevar],scale),prep.meth=DB[,"prep.meth"],article=DB[,"article"],X.MeOH=DB[,"X.MeOH"],S.MeOH=DB[,"S.MeOH"],Y.MeOH=DB[,"Y.MeOH"])
DBs<-DBs[,names(DB)] # to get the original order back

#encode responses to fractions
DBs[(length(DBs)-2):length(DBs)]<-DBs[(length(DBs)-2):length(DBs)]/100

#save standardized data base
write.csv(DBs, file = "MeOH st xsy article.csv",row.names=FALSE)