An answer to 1)
> x = data.frame(Type=c('A','A','B','B'), ID=c(1,1,3,1), Date =
c('16/09/2010','23/09/2010','18/8/2010','13/5/2010'), Value=c(8,9,7,6))
> x
Type ID Date Value
1 A 1 16/09/2010 8
2 A 1 23/09/2010 9
3 B 3 18/8/2010 7
4 B 1 13/5/2010 6
> x$Date = as.Date(x$Date,format='%d/%m/%Y')
> library(plyr)
> x$uniqueID = paste(x$Type, x$ID, sep='')
> nobs = daply(x, ~uniqueID, nrow)
> keep = names(nobs)[nobs>1]
> newx = x[x$uniqueID %in% keep,]
An answer to 2)
> require(plyr)
> ddply(newx, ~uniqueID, transform, newDate = as.numeric(Date -
min(Date)+1))
On 08/24/2010 01:19 PM, Chris Beeley wrote:
Hello-
A basic question which has nonetheless floored me entirely. I have a
dataset which looks like this:
Type ID Date Value
A 1 16/09/2020 8
A 1 23/09/2010 9
B 3 18/8/2010 7
B 1 13/5/2010 6
There are two Types, which correspond to different individuals in
different conditions, and loads of ID labels (1:50) corresponding to
the different individuals in each condition, and measurements at
different times (from 1 to 10 measurements) for each individual.
I want to perform the following operations:
1) Delete all individuals for whom only one measurement is available.
In the dataset above, you can see that I want to delete the row Type B
ID 3, and Type B ID 1, but without deleting the Type A ID 1 data
because there is more than one measurement for Type A ID 1 (but not
for Type B ID1)
2) Produce difference scores for each of the Dates, so each individual
(Type A ID1 and all the others for whom more than one measurement
exists) starts at Date "1" and goes up in integers according to how
many days have elapsed.
I just know there's some incredibly cunning R-ish way of doing this
but after many hours of fiddling I have had to admit defeat.
I would be very grateful for any words of advice.
Many thanks,
Chris Beeley,
Institute of Mental Health, UK
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--
Abhijit Dasgupta, PhD
Director and Principal Statistician
ARAASTAT
Ph: 301.385.3067
E: adasgu...@araastat.com
W: http://www.araastat.com
______________________________________________
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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.
