Update logranktest.R

R/logranktest.R

@@ -12,7 +12,6 @@
 #' logranktest(time = time, event = event, group = group)
 logranktest <- function(time, event, group) {
   n <- length(time)
-  # ng <- table(group)
   group <- factor(group)
   Ag <- stats::aggregate(event,
     by = list(time = time, group = group),
@@ -27,34 +26,16 @@ logranktest <- function(time, event, group) {
   tab$atrisk1 <- NA
   tab$atrisk2 <- NA
 
-  # browser()
-  # for (i in 1:dim(tab)[1]) {
   tab$atrisk1 <- unlist(lapply(tab$time, function(x) sum(time[group == levels(group)[1]] >= x)))
-  # tab$atrisk1[i]<-sum(time[group == unique(group)[1]] >=tab$time[i])
   tab$atrisk2 <- unlist(lapply(tab$time, function(x) sum(time[group == levels(group)[2]] >= x)))
-  # tab$atrisk2[i]<-sum(time[group == unique(group)[2]] >=tab$time[i])
-  # }
-  # nz <- dim(tab)[1]
   tab$atrisk <- tab$atrisk1 + tab$atrisk2
   tab$event <- tab$event1 + tab$event2
   D <- tab[tab$event > 0, ]
-  D$expected1 <- D$event * D$atrisk1 / D$atrisk
-  # D$expected2 <- D$event * D$atrisk2/D$atrisk
+  D$expected1 <- D$event * D$atrisk1 / D$atrisk 
   D$diff1 <- D$event1 - D$expected1
   D$var <- D$atrisk1 * D$event * D$atrisk2 * (D$atrisk - D$event) / (D$atrisk^2 *
     (D$atrisk - 1))
-  # D$S <- cumprod((D$atrisk - D$event)/D$atrisk)
-  # Dvoll <- D
   D <- D[D$atrisk1 > 0 & D$atrisk2 > 0, ]
-  z <- sum(D$diff1) / sqrt(sum(D$var))
-  # Chisq <- (sum( D$diff1))^2/sum( D$var)
-  # 27
-  # df <- nlevels(group) - 1
-  # p <- 1 - pchisq(Chisq, df = df)
-  # out = list(D = D, test = data.frame( z, Chisq, df, p),
-  #          var = sum(D$var), obs = c(sum(D$event1),
-  #                                   sum(D$event2)), exp = c(sum(D$expected1), sum(D$expected2)),
-  #        n = c(sum(D$atrisk1[1]), sum(D$atrisk2[1])))
-  # class(out) = "logrank"
+  z <- sum(D$diff1) / sqrt(sum(D$var)) 
   return(z)
 }