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analysing data with case weights: rejoinder

4 messages · Michal Bojanowski, Peter Dalgaard, Thomas Lumley

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Hello,

Based on replies (which I'm gratefull for) I guess the only solution
is to create a package, that will contain function to build
lm()-like linear models, and allow weighting cases (as I described
two days ago).

This would also alow buliding those models for data in aggregated
form without a need for using e.g. expand$grid().

Thank you again for replies.

  

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Michal Bojanowski       mailto:mbojanowski at samba.iss.uw.edu.pl
Polish General Social Survey
Institute for Social Studies
University of Warsaw
http://www.iss.uw.edu.pl/

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On Fri, 15 Nov 2002, bojaniss wrote:

            
There's no problem with data in aggregated form, only with probability
weighting.

	-thomas


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Thomas Lumley <tlumley at u.washington.edu> writes:
Depends on what you mean with "aggregation" doesn't it? If you have
"replication weights" (counts of data with given value), I think you
still have problems.
#
On 15 Nov 2002, Peter Dalgaard BSA wrote:

            
There's no problem for categorical data, which is the case where you
most likely to have counts of data with given value.

With a linear model you can aggregate further to get an average value over
each covariate pattern and then have variance weights


	-thomas

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