# st: Using -collapse- extensively to find historical, irregular matches: Better way?

 From "Chih-Mao Hsieh" To Subject st: Using -collapse- extensively to find historical, irregular matches: Better way? Date Tue, 30 Sep 2003 09:20:41 -0500

```Hi all,

I have a two-column file with variables "citing" and "cited".  "Citing" refers to a patent, and "cited" refers to a patent that is "cited" by the "citing" patent.  Therefore, if a patent cites and therefore "recombines" 3 patents prior to it, this history shows up as 3 rows (end of message has examples).

I need a program to catch the number of times that the exact same set of patents has been "recombined" in the past (i.e. imagine trying to find all the papers that cite the same set of references that you do in one of your papers!).

The basic solution I have come up with is the following:

collapse (mean) mean=cited (sum) sum=cited (sd) sd=cited, by(citing)
bysort mean sum sd: gen byte counter = _n
replace counter=counter-1

It seems to work, and as the datafile has 16 million rows, with 3 million unique "citing" numbers -- therefore with a fair amount of variance -- I believe it may be good enough.  My questions are: (1) Is there a more accurate way, if less efficient, to do what I need? (2) Is there any reason I should expect Stata to calculate means, sums, and sd's in different ways from row to row (i.e. rounding) that would render totally ineffective my specific use of -collapse-?  I attach an example below.

Thanks, --Chihmao

------------------------------------------

citing      cited
100          30
100          32
100          33
101          34
101          35
105          30
105          32
105          33
106          29
106          30
108          30
108          32
108          33

Desired output:

citing      counter
100            0
101            0
105            1    (since #100 cited the exact same list of patents, no more, no less)
106            0
108            2    (since there are now 2 prior occurrences of same patent list: #100 and #105)

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```