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Re: st: Obtaining predictions with margeff & gologit2


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu, "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Obtaining predictions with margeff & gologit2
Date   Sun, 21 Apr 2013 10:37:07 -0500

Unfortunately gologit2 does not support factor variables. But, if you are careful you can use the -margins- command to get predicted probabilities. For example, the following gives you adjusted predictions for whites:

webuse nhanes2f,clear
gologit2 health age black orace
margins, at(black = 0 orace=0) predict(outcome(#1))
margins, at(black = 0 orace=0) predict(outcome(#2))
margins, at(black = 0 orace=0) predict(outcome(#3))
margins, at(black = 0 orace=0) predict(outcome(#4))
margins, at(black = 0 orace=0) predict(outcome(#5))

If you prefer to use means for age and other variables, you could add the -atmeans- option.

At 01:20 PM 4/19/2013, Tiainen Ossi wrote:
Hello,

I'm using the gologit2 generalized logistic regression/ partial proportional odds model for ordinal dependent variables. The dependent variable describes firm size and is a categorical variable with three groups, small, medium and large. Independent variables are three dummies that describe categorical firm types + some control variables.

I used margeff to get the average marginal effect coefficients (see output below), but i'm having difficulties in understanding how I could get the predicted probabilities for the three dummies in a convenient way. For mlogit the 'margins' command gives the probabilities directly, so is there some way to obtain them with gologit2 or must I use the predict command and calculate the probabilities by hand for each dummy?

If I use predict, how can I get the base probability level that the three coefficients below are compared to? What about if I use marginal effects at mean instead of average marginal effects?

Thank you for your assistance in advance!

Best regards,
Ossi Tiainen


. margeff, dummies(Iprsv* \ Ipscl* \ Icountry* \ Inace*)

Average partial effects after gologit2

y  =3D Pr(size04)
--------------------------------------------------------------------------------
variable | Coef. Std. Err. z P>|z| [95% Conf. Interval=]
---------------+-----------------------------------------------------------------------+---=-----
Small        |
Iprsvinn_1 |  -.1368403   .0136474   -10.03   0.000    -.1635887   -.1100918
Iprsvinn_2 |  -.0130166   .0185622    -0.70   0.483    -.0493979    .0233646
Iprsvinn_3 |  -.0665578   .0193864    -3.43   0.001    -.1045544   -.0285611

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Richard Williams, Notre Dame Dept of Sociology
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