Hi,
I have a data set in which the variable 'dose' is time-varying. Currently,
the data set is in a long format, with 1 row for each time unit of follow-up
for each individual "Id". It looks like this:
orig.data <- cbind(Id = c(rep(1,4), rep(2,5)), time = c(1:4, 1:5), dose =
c(1,1,1,0,1,0,1,1,0))
orig.data
Id time dose
[1,] 1 1 1
[2,] 1 2 1
[3,] 1 3 1
[4,] 1 4 0
[5,] 2 1 1
[6,] 2 2 0
[7,] 2 3 1
[8,] 2 4 1
[9,] 2 5 0
What I would like to do is to convert the data set into an interval format.
By that I mean a data set in which each row has a 'Start' and a 'Stop' value
that indicates the time units in which the 'dose' is constant. For example,
my orig.data example would now be:
int.data <- cbind(Id = c(rep(1,2), rep(2,4)), Start = c(1,4,1,2,3,5), Stop
= c(3,4,1,2,4,5), dose = c(1,0,1,0,1,0))
int.data
Id Start Stop dose
[1,] 1 1 3 1
[2,] 1 4 4 0
[3,] 2 1 1 1
[4,] 2 2 2 0
[5,] 2 3 4 1
[6,] 2 5 5 0
Basically, this implies collapsing rows that have the same "Id" and "dose"
and creating "Start" and "Stop" to index the time.
While I can write a clumsy routine with multiple loops to do it, it will be
inefficient and will not work for large data set.
I wonder if people know of a function that would reshape my data set from
'long' to 'interval'?
Best,
MP
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