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From |
"Chih-Mao Hsieh" <Hsieh@olin.wustl.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

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) * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: Using -collapse- extensively to find historical, irregular matches: Better way?***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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