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Re: st: treatment of missing values in a matrix dissimilarity score

From   "Eva Poen" <[email protected]>
To   [email protected]
Subject   Re: st: treatment of missing values in a matrix dissimilarity score
Date   Mon, 15 Sep 2008 20:49:49 +0100


Stata seems to do listwise deletion, which appears fair in this
situation; it is not clear to me how comparable similarity measures
would be between observations when they are calculated based on
different sets of variables.

You want to calculate similarities only across non-missing elements. I
don't think there is an easy way to do this. One approach is to enlist
the help of -mvpatterns- which you can locate using -findit-.
-mvpatterns x1 x2 x3 x4- will tell you which patterns of missing
values exist in your data. You can then run the -matrix dissimilarity-
command separately for each pattern:

matrix dissimilarity m1=x1 x3 if x2 >=. & x4 >=., match proportion

for example, for all those observations that have x1 and x3
non-missing but x2 and x4 missing.


2008/9/15 Elkins, Zachary S <[email protected]>:
> I'd like to calculate the matches between observations across a set of binary variables.  I suspect that there are multiple ways to do this.  I've specified:
> matrix dissimilarity m=x1 x2 x3 x4, match proportion
> However, some values in x1-x4 are missing.  Based on the results, it appears that Stata treats missing values as if they were 1 and I don't see how to modify that.  I'd like to calculate to calculate similarities across only non-missing elements (the number of which will be different for each pair, of course).
> Thanks for any help.
> Zach Elkins
> ______________________________
> Zachary Elkins
> Assistant Professor
> Department of Government
> University of Texas at Austin
> 1 University Station A1800
> Austin, TX  78712-0119
> p: (512) 232-7250
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