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Re: st: imputing continuous values when respondents select categories, e.g., income category


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>, "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: imputing continuous values when respondents select categories, e.g., income category
Date   Mon, 27 Apr 2009 01:35:08 -0500

At 02:38 PM 4/26/2009, Clive Nicholas wrote:
(Slight change of subject, but...)

Richard Williams replied to Jay Verkuilen:

> Indeed, as the -intreg- documentation notes, -intreg- is a generalization of
> the models fit by -cnreg- and -tobit-.

Really? Does this implicate -xtintreg- as well? I only ask because
I've recently used -xtintreg- to fit pooled TSCS models with an
ordinal-level dependent variable (the nearest best thing in Stata
9.2), and even then you have to assume random effects when using it
(unfortuately, there is no fixed-effect equivalent; but with my
football data, this condition wasn't too restrictive, and I could
always circumvent it by mean-centering). However, although my ODV
contained lots of 0s, it was not in any way censored.

I am not sure what you mean by "implicate" but I suppose that most or all of what is true of intreg is also true for xtintreg. Also, I wonder about your statement that the data are in no way censored. I think the lower and upper bounds are supposed to be regarded as negative and positive infinity, even if in practice the observed range is much more limited than that.

FYI, I have a hypothetical example where intreg works spectacularly well:

http://www.nd.edu/~rwilliam/xsoc73994/intreg3.pdf

However, as noted in the handout, everything is set up so intreg's assumptions are met. A simulation analysis examining how well it worked when assumptions were violated would no doubt be useful.


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Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
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EMAIL:  Richard.A.Williams.5@ND.Edu
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