Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down at the end of May, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

RE: st: Interaction in logit


From   "Mustillo, Sarah A" <smustill@purdue.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Interaction in logit
Date   Mon, 25 Oct 2010 08:51:32 -0400

In addition to Maartin's Stata Tip #87, UCLA also has some nice tutorials on using -margins- to interpret interactions in logistic regression.

For continuous by continuous:

http://www.ats.ucla.edu/stat/stata/faq/logitconcon.htm

For categorical by continuous:

http://www.ats.ucla.edu/stat/stata/faq/logitcatcon11.htm


For multiple interactions:

http://www.ats.ucla.edu/stat/stata/faq/margins_mlogcatcon.htm


Sarah

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten buis
Sent: Monday, October 25, 2010 8:44 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Interaction in logit

--- On Mon, 25/10/10, Teemu.Kautonen@tse.fi wrote:
> My colleagues and I are working on an analysis where we
> have a dummy moderator and three continuous IVs which the
> dummy is hypothesised to moderate. The dependent variable is
> a dummy and we estimated a logit model. 
> 
> We have run the analysis both using the -inteff- command by
> Ed Norton and his colleagues and by analysing the odds
> ratios, as advised by Jaccard (2001). 
<snip> 
> Does anyone have more experience with this type of analysis
> and with these two approaches to analysing interactions in
> binary regression? 

Please give complete references. This is a multi-disciplinary
list, and literature you assume so universally well known that
a "name-year" reference will suffice is likely to be completely 
unknown in other disciplines.

Interactions in terms of odds ratios and marginal effects are 
subtly different, in that odds ratios are effects in relative 
terms with respect to the baseline odds while marginal effects 
are absolute effects. This means that the interaction effects 
as computed by -inteff- are sensitive to differences in the 
baseline odds, while the interaciton effects in terms of the 
ratio of odds ratios is not sensitive to this difference. 
Sensitivity with respect to differences in the baseline odds 
is not necesarily a bad thing, it is a substantive quesiton 
whether or not you want to control for that. I wrote an 
example of that in:

M.L. Buis (2010) "Stata tip 87: Interpretation of interactions 
in non-linear models", The Stata Journal, 10(2), pp. 305-308.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------


      

*
*   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/

*
*   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/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index