I'm trying to make some survival analysis with an ordered categorical variable using the test for trend option in ggsurvplot function from survminer package. The p value obtained is different if my variable is numeric (1,2,3,4) or an ordered factor ("1","2","3","4") when computing log rank test for trend. Which format should I used and why?
I also used the comp function from survMisc package because it seems that ggsurvplot is based on this package and obtained as expected the same results.
Thank you very much for your help.
This is a code to reproduce the issue:
library(survminer)
data("larynx", package="KMsurv")
larynx.table=larynx
larynx.table$stage.cat=as.character(larynx.table$stage)
larynx.table$stage.fact=factor(larynx.table$stage.cat,levels=c("1","2","3","4"))
larynx.table$stage.fact.inv=factor(larynx.table$stage.cat,levels=c("4","3","2","1"))
fit1<- survfit(Surv(time, delta) ~ stage, data = larynx.table)
fit2<- survfit(Surv(time, delta) ~ stage.cat, data = larynx.table)
fit3<- survfit(Surv(time, delta) ~ stage.fact, data = larynx.table)
fit4<- survfit(Surv(time, delta) ~ stage.fact.inv, data = larynx.table)
SA=ggsurvplot(fit1, data = larynx.table, pval = TRUE,test.for.trend = TRUE)
SB=ggsurvplot(fit2, data = larynx.table, pval = TRUE,test.for.trend = TRUE)
SD=ggsurvplot(fit3, data = larynx.table, pval = TRUE,test.for.trend = TRUE)
SE=ggsurvplot(fit4, data = larynx.table, pval = TRUE,test.for.trend = TRUE)
arrange_ggsurvplots(list(SA,SB,SD,SE),ncol=2,nrow=2)
