I have a datset that looks something like this:
> head(BurnData)
Treatment Gender Race Surface head buttock trunk up.leg low.leg resp.tract type ex.time excision antib.time antibiotic
1 0 0 0 15 0 0 1 1 0 0 2 12 0 12 0
2 0 0 1 20 0 0 1 0 0 0 4 9 0 9 0
3 0 0 1 15 0 0 0 1 1 0 2 13 0 13 0
4 0 0 0 20 1 0 1 0 0 0 2 11 1 29 0
5 0 0 1 70 1 1 1 1 0 0 2 28 1 31 0
6 0 0 1 20 1 0 1 0 0 0 4 11 0 11 0
inf.time infection
1 12 0
2 9 0
3 7 1
4 29 0
5 4 1
6 8 1
I want to run a Cox's Regression on variables Surface, ex.time and, antib.time and treatment. Treatment is an indicator variable. Surface denotes the % of body burned. ex.time and antib.time both record time to event in days.
I am aware that to run a time dependent Cox's Regression i need to convert the data in longitudinal structure, but how can i do it in R?
then i will use the forluma:
coxph(formula = Surv(tstart, tstop, infection) ~ covariate)
DATA
> dput(head(BurnData))
structure(list(Treatment = c(0L, 0L, 0L, 0L, 0L, 0L), Gender = c(0L,
0L, 0L, 0L, 0L, 0L), Race = c(0L, 1L, 1L, 0L, 1L, 1L), Surface = c(15L,
20L, 15L, 20L, 70L, 20L), head = c(0L, 0L, 0L, 1L, 1L, 1L), buttock = c(0L,
0L, 0L, 0L, 1L, 0L), trunk = c(1L, 1L, 0L, 1L, 1L, 1L), up.leg = c(1L,
0L, 1L, 0L, 1L, 0L), low.leg = c(0L, 0L, 1L, 0L, 0L, 0L), resp.tract = c(0L,
0L, 0L, 0L, 0L, 0L), type = c(2L, 4L, 2L, 2L, 2L, 4L), ex.time = c(12L,
9L, 13L, 11L, 28L, 11L), excision = c(0L, 0L, 0L, 1L, 1L, 0L),
antib.time = c(12L, 9L, 13L, 29L, 31L, 11L), antibiotic = c(0L,
0L, 0L, 0L, 0L, 0L), inf.time = c(12L, 9L, 7L, 29L, 4L, 8L
), infection = c(0L, 0L, 1L, 0L, 1L, 1L), Surface_discr = structure(c(1L,
1L, 1L, 1L, 2L, 1L), .Label = c("1", "2"), class = "factor"),
ex.time_discr = c(1L, 1L, 1L, 1L, 2L, 1L), antib.time_discr = c(1L,
1L, 1L, 2L, 2L, 1L)), .Names = c("Treatment", "Gender", "Race",
"Surface", "head", "buttock", "trunk", "up.leg", "low.leg", "resp.tract",
"type", "ex.time", "excision", "antib.time", "antibiotic", "inf.time",
"infection", "Surface_discr", "ex.time_discr", "antib.time_discr"
), row.names = c(NA, 6L), class = "data.frame")
