# (iii) Determine variable importance Determine variable importance for continuous, categorical or right-censored survival endpoints (overall and per treatment group) using random forests ```r subscreenvi(data, y, cens = NULL, x = NULL, trt = NULL) ``` ## Arguments - `data`: The data frame containing the dependent and independent variables. - `y`: The name of the column in `data` that contains the dependent variable. - `cens`: The name of the column in `data` that contains the censoring variable, if `y` is an event time (default=NULL). - `x`: Vector that contains the names of the columns in `data` with the independent variables (default=NULL, i.e. all remaining variables) - `trt`: The name of the column in `data` that contains the treatment variable (default=NULL). ## Returns A list containing ordered data frames with the variable importances (one for each treatment level, one with the ranking variability between the treatment levels and one with the total results) ## Examples ```r ## Not run: require(survival) data(pbc, package="survival") # generate categorical versions of some of the baseline covariates pbc$ageg[!is.na(pbc$age)] <- ifelse(pbc$age[!is.na(pbc$age)] <= median(pbc$age, na.rm=TRUE), "Low", "High") pbc$albuming[!is.na(pbc$albumin)]<- ifelse(pbc$albumin[!is.na(pbc$albumin)] <= median(pbc$albumin, na.rm=TRUE), "Low", "High") pbc$phosg[!is.na(pbc$alk.phos)] <- ifelse(pbc$alk.phos[!is.na(pbc$alk.phos)]<= median(pbc$alk.phos,na.rm=TRUE), "Low", "High") pbc$astg[!is.na(pbc$ast)] <- ifelse(pbc$ast[!is.na(pbc$ast)] <= median(pbc$ast, na.rm=TRUE), "Low", "High") pbc$bilig[!is.na(pbc$bili)] <- ifelse(pbc$bili[!is.na(pbc$bili)] <= median(pbc$bili, na.rm=TRUE), "Low", "High") pbc$cholg[!is.na(pbc$chol)] <- ifelse(pbc$chol[!is.na(pbc$chol)] <= median(pbc$chol, na.rm=TRUE), "Low", "High") pbc$copperg[!is.na(pbc$copper)] <- ifelse(pbc$copper[!is.na(pbc$copper)] <= median(pbc$copper, na.rm=TRUE), "Low", "High") pbc$ageg[is.na(pbc$age)] <- "No Data" pbc$albuming[is.na(pbc$albumin)] <- "No Data" pbc$phosg[is.na(pbc$alk.phos)] <- "No Data" pbc$astg[is.na(pbc$ast)] <- "No Data" pbc$bilig[is.na(pbc$bili)] <- "No Data" pbc$cholg[is.na(pbc$chol)] <- "No Data" pbc$copperg[is.na(pbc$copper)] <- "No Data" #eliminate treatment NAs pbcdat <- pbc[!is.na(pbc$trt), ] pbcdat$status <- ifelse(pbcdat$status==0,0,1) importance <- subscreenvi(data=pbcdat, y='time', cens='status', trt='trt', x=c("ageg", "sex", "bilig", "cholg", "copperg")) ## End(Not run) ```

subscreenvi function