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Re: st: Re: Ordinal independent variables in probit regression


From   Richard Williams <[email protected]>
To   [email protected], <[email protected]>
Subject   Re: st: Re: Ordinal independent variables in probit regression
Date   Wed, 09 Apr 2014 23:09:32 -0500

You could do something like this:

webuse nhanes2f, clear
probit diabetes i.health
est store m1
probit diabetes health
est store m2
lrtest m1 m2

If the contrast is not significant you can treat the variable as continuous.

Incidentally, it doesn't particularly matter that probit is being used; the same sorts of approaches could be used for regress.

Joseph, I am not that good with the contrast command, so I wouldn't mind seeing examples of how it could be used instead.

At 07:15 PM 4/9/2014, Joseph Coveney wrote:
Nyasha Tirivayi wrote:

How best can I use a likert scale/ordered predictor in a probit
regression? The variable has five response categories from Strongly
disagree to Agree (neutral is the third response option).

Should I include the variable as it is, where one category becomes the
reference? Or should I consider the variable to be continuous? Or
should I instead use the tab command to create dummies for all five
response options, and include the ones I am interested in ( e.g.
strongly agree and agree responsea)?

--------------------------------------------------------------------------------

There are numerous ways to include it as a predictor.  You could use factor
variables and then use -contrast- after fitting the model.  You could put the
scores in linearly (as a continuous predictor).  But it seems that you've
already hit upon the way that makes most sense from the standpoint of how best
to address the question of scientific interest:  create three indicator
variables, one for strongly agree, one for agree, and one for all of the other
scores--something like that below.  (You can accomplish the same thing using a
factor variable and then constructing particular contrasts of interest after
fitting the model.)

    generate byte strongly_agree = likertlike_score == "Strongly Agree"
    generate byte agree = likertlike_score == "Agree"
    generate byte others = !strongly_agree & !agree
   probit response c.(strongly_agree agree others)

Joseph Coveney

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Richard Williams, Notre Dame Dept of Sociology
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