I can see two alternative strategies (there may well be more):
1) You can consider this a missing data problem and try multiple
imputation, like in:
Patrick Royston (2007) Multiple imputation of missing values: further
update of ice, with an emphasis on interval censoring. The Stata
Journal, 7(4): 445-464.
http://stata-journal.com/article.html?article=st0067_3
2) Alternatively you can scale the income variable such that it
optimally predicts the outcome variable like in:
Maarten L. Buis (2008) Scaling levels of eduction.
http://home.fsw.vu.nl/m.buis/
and
Usefulness and estimation of proportionality constraints: The
propcnsreg package. presented at the 13th UK Stata Users Group Meeting
on September 10 2007 in London. http://home.fsw.vu.nl/m.buis/
Hope this helps,
Maarten
--- "Jessica A.Jakubowski" <[email protected]> wrote:
> I have data that includes an income variable measured at the interval
> level, e.g.:
> 1= less than $10,000
> 2= $10,000-$15,000
> 3= $15,000-$20,000
> 4= $20,000-$25,000
> 5= $25,000-$35,000
> 6= $35,000-$50,000
> 7= $50,000-$75,000
> 8= over $75,000
>
> Stata has a way to deal with interval data when it is a dependent
> variable in a regression model with the command -intreg-
>
> I would like to know if Stata has a way to deal with interval
> variables on the right-hand side of the regression equation, that is,
> as an independent variable. I am using this interval income variable
> in models with continuous (-regress-) and binary (-logit-)
> outcomes. Right now, I am using the midpoint of the intervals (and
> the open top interval*1.5), but I'm wondering if there's a better
way.
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room N515
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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