# Re: st: -graph twoway (function ...)- question

 From Andrea Bennett To statalist@hsphsun2.harvard.edu Subject Re: st: -graph twoway (function ...)- question Date Thu, 24 Jul 2008 18:03:18 +0200

Thanks for this hint, I didn't know your app!

But, after having played around with it, I fear it is not possible to have multiple probability lines in one graph? E.g. I would want to show the change in the probability but for each of the three age categories separately (but in one graph). Is this possible? Would I need to deal with the -save- option? And last, it seem not possible to display confidence intervals, right?

When I would like to display changes in probabilities, what else is available as an option. I know the prvalue/praccum command which I will try next. Any good input is welcomed, though!

Kind regards,

Andrea

P.S. In your help file, in the "examples" section, there is a line "oprobpr mpg, adj(weight=2500, foreign=0)" while the option -adj- is not discussed (and does not work).

On Jul 24, 2008, at 3:37 PM, Nick Winter wrote:

I don't have an answer to your specific question, but another way to go is to plot predicted probabilities. My -oprobpr- package might help for this. (-oprobpr- only works after -oprobit- not -probit-, but oprobit will estimate the same model as probit if there are only two response categories; just use the -categories()- option to specify which response category you want plotted.

-Nick Winter

Andrea Bennett wrote:

Dear all,
I have estimated average marginal effects from a probit regression with -margeff- and would like to generate a graph which plots the marginal effects for 3 age categories (dummies) dependent on a continuous variable called cont.
The model is as such:
y = b0 + b1*age2 + b2*age3 + b3*age2*cont +b4*age3*cont + b5*cont + controls
As age2 and age3 are dummies, would the following graph command be correct:
twoway (function age1 = _b[cont]*x, range(0 0.5)) (function age2 = _b[age2] + (_b[cont] + _b[cont_age2])*x, range(0 0.5)) (function age3 = _b[age3] + (_b[cont] + _b[cont_age3])*x, range(0 0.5))
The way I understand it, since I have now marginal effects I can work equivalently to linear models. Then the above graph should be correct, right? Further, this would also be correct when introducing other interactions with -cont- as long as I am looking at the marginal effects of age groups when -cont- changes?
Many thanks for your considerations,
Andrea
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