R help - Mar 2010 - Converting a data set from 'long' format to 'interval' format

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

	[[alternative HTML version deleted]]

Try this:

foo <- function(x) {
		data.frame(Id = unique(x$Id), rbind(range(x$time)), dose = unique(x$dose))
}

t(sapply(split(as.data.frame(orig.data),
               with(rle(orig.data[,'dose']), rep(seq_along(lengths),
lengths))),
	   foo))

On Wed, Mar 24, 2010 at 12:27 PM, Marie-Pierre Sylvestre
<mp.sylvestre at gmail.com> wrote:
> 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
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
Henrique Dallazuanna
Curitiba-Paran?-Brasil
25? 25' 40" S 49? 16' 22" O