Have you considered "cbind" and "rbind"? If your data.frame has
factors, they could present problems with "rbind". Try
'sapply(tenn.dat, class)'. If you have only class character or numeric,
use "cbind" to match the columns of tenn.dat both in name and class,
then use "rbind" to combine it with the original.
hope this helps. spencer
Doran, Harold wrote:
I am working with a longitudinal data set in the long format. This data
set has three observations per grade level per year. Here are the first
10 rows of the data frame:
tenn.dat[1:10,]
year schid type grade gain se new cohort
6 2001 100005 5 4 33.1 3.5 4 3
7 2002 100005 5 4 33.9 3.9 4 2
8 2003 100005 5 4 32.3 4.2 4 1
10 2001 100005 5 5 22.9 4.0 5 4
11 2002 100005 5 5 25.0 3.4 5 3
12 2003 100005 5 5 7.8 3.8 5 2
18 2001 100010 1 4 34.4 5.9 4 3
19 2002 100010 1 4 27.8 5.6 4 2
20 2003 100010 1 4 34.6 6.8 4 1
22 2001 100010 1 5 21.1 4.8 5 4
I need to create a new column in this data frame with the mean gain for
each grade by year and the sd for each grade by year.
So, I used tapply as follows:
tapply(tenn.dat[,5],tenn.dat[,c(1,4)],mean) and
tapply(tenn.dat[,5],tenn.dat[,c(1,4)],sd) which produces exactly the
data I would like to attach in column 1 and 2 respectively.
I am having a problem connecting this back with the corresponding rows
in the data frame.
If I used only one factor instead of two, I was successful connecting
this with the data frame using:
m.gain<-tapply(tenn.dat[,5],tenn.dat[,4],mean)
tenn.dat$m.gain<-m.gain[as.character(tenn.dat$grade)]
can anyone offer suggestions on a next step?
Thanks,
Harold
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