Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: MIXLOGIT: marginal effects
From
Richard Williams <[email protected]>
To
[email protected], [email protected]
Subject
Re: st: MIXLOGIT: marginal effects
Date
Mon, 06 Feb 2012 13:01:43 -0500
At 12:42 PM 2/6/2012, Maarten Buis wrote:
On Mon, Feb 6, 2012 at 6:25 PM, Arne Risa Hole wrote:
> Thanks Maarten, I take your point, but as Richard says there is
> nothing stopping you from calculating marginal effects at different
> values of the explanatory variables (although admittedly it's rarely
> done in practice).
That is fine, but in that case I would be reporting/plotting predicted
probabilities rather than marginal effects. There is not a big
difference between the two --- the latter is just the first derivative
of the former --- but if you are going to report multiple numbers than
the former seems more direct to me.
Anyhow, as you said, this is typically not what people (or reviewers,
advisers, etc.) want; they just want to know what "the" effect is and
not be bothered with multiple different effects. In that case my
previous post applies and marginal effects are (almost) always the
wrong choice.
I think knowing the mean of a variable is useful, e.g. is the mean
income $30K or is it $60K? Likewise I think knowing the AME (Amerage
Marginal Effect) is useful, e.g. is the average difference between
blacks and whites 5% or is it 50%? In neither case do I think the
number tells you everything you could want to know but it tells you something.
Likewise I think an odds ratio can be helpful, but to make it really
helpful it is useful to see how predictions differ across baseline
levels, e.g it makes a difference whether the baseline odds are a
million to 1 or 1:1, and these baseline odds will differ across
individuals. Personally, I find it more helpful to see predicted
probabilities or differences in predicted probabilities, but any
number of things are better than just looking at coefficients from
something like logit which have little intuitive appeal to most people.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/