On Thu, 10 Sep 2009, Irwin, James R wrote: Welcome to the gretl list, and I hope we can help you to migrate without too much pain! I have to admit that Stata's "collapse" command seems oddly specific to me -- I mean, I wouldn't have thought that such an apparently specialized operation would merit a command to itself. But maybe that just shows lack of imagination on my part! Anyway, yes, gretl can do this sort of thing but you have to roll your own "collapse". My approach below is to create a matrix containing the "collapsed" values, then substitute this matrix for the current dataset. For illustration I'm using a stylized version of the dataset you describe, namely this plain text file <collapse.txt> obs YEAR X2 1 1950 1 2 1950 2 3 1950 3 4 1950 4 5 1951 2 6 1951 NA 7 1951 4 8 1951 5 9 1952 3 10 1952 4 11 1952 5 12 1952 6 13 1952 7 </collapse.txt> Note that I've thrown in a missing observation ("NA") just for fun. Now here's the gretl script to do the job (without the explanations this could be a lot more compact): <script> open collapse.txt # make a matrix containing the distinct values of YEAR matrix yrvals = values(YEAR) # and find out how many values there are scalar nvals = rows(yrvals) # then allocate an appropriately sized zero matrix matrix newdata = zeros(nvals, 3) # now fill the 'newdata' matrix loop i=1..nvals # restrict the sample to the given YEAR smpl (YEAR = yrvals[i]) --restrict # record the YEAR we're looking at newdata[i,1] = yrvals[i] # count the (non-missing) observations on X2 newdata[i,2] = sum(ok(X2)) # and record the mean of X2 newdata[i,3] = mean(X2) # re-establish the full data range for next iteration smpl --full endloop # create a new dataset with the right number of observations, # preserving current matrices nulldata nvals --preserve # and dump out the columns of 'newdata' into series series YEAR = newdata[,1] series X2count = newdata[,2] series X2avg = newdata[,3] # then see what we got print YEAR X2count X2avg --byobs </script> Allin Cottrell