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Thank you for your excellent work! I found that the subgroup variables of the resulting table would not match the results. For example:
library(survival) library(dplyr) lung %>% mutate( status = as.integer(status == 1), sex = factor(sex), kk = factor(as.integer(pat.karno >= 70)), kk1 = factor(as.integer(pat.karno >= 60)) ) -> lung Coxlung <- TableSubgroupMultiCox(Surv(time, status) ~ sex, var_subgroups = c("kk", "kk1"), data = lung, time_eventrate = 100, line = TRUE )
Coxlung
But in reality, the result of the "0" in kk is actually the result of the "1".
Use table(lung$kk , useNA = 'ifany') to verify the results:
table(lung$kk , useNA = 'ifany') 0 1 38 187 3
The results also match confusingly when the subgroup variables are three or even four. Thank you for debugging it.
The text was updated successfully, but these errors were encountered:
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Thank you for your excellent work! I found that the subgroup variables of the resulting table would not match the results.
For example:
library(survival)
library(dplyr)
lung %>%
mutate(
status = as.integer(status == 1),
sex = factor(sex),
kk = factor(as.integer(pat.karno >= 70)),
kk1 = factor(as.integer(pat.karno >= 60))
) -> lung
Coxlung <- TableSubgroupMultiCox(Surv(time, status) ~ sex,
var_subgroups = c("kk", "kk1"),
data = lung, time_eventrate = 100, line = TRUE
)
Coxlung
But in reality, the result of the "0" in kk is actually the result of the "1".
Use table(lung$kk , useNA = 'ifany') to verify the results:
The results also match confusingly when the subgroup variables are three or even four.
Thank you for debugging it.
The text was updated successfully, but these errors were encountered: