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: Presenting Interaction in LR
From
Jana von Stein <[email protected]>
To
[email protected]
Subject
Re: st: Presenting Interaction in LR
Date
Thu, 8 Dec 2011 16:47:26 -0500
Consider some of the resources here: https://files.nyu.edu/mrg217/public/interaction.html
Jana
On Dec 8, 2011, at 2:35 PM, Cameron McIntosh wrote:
I would also suggest looking at the following for additional
guidance on how to examine and discuss your interaction effects:
Hayes, A.F., & Matthes, J. (2009). Computational procedures for
probing interactions in OLS and logistic regression: SPSS and SAS
implementations. Behavior Research Methods, 41, 924-936. http://www.personal.psu.edu/jxb14/M554/articles/Hayes&Matthes2009.pdf
Aguinis, H, & Gottfredson, R. K. (2010). Best-practice
recommendations for estimating interaction effects using moderated
multiple regression. Journal of Organizational Behavior, 31, 776-786.http://mypage.iu.edu/~haguinis/JOB2010.pdf
Shieh, G. (2011). Clarifying the role of mean centering in
multicollinearity of interaction effects. British Journal of
Mathematical and Statistical Psychology, 64(3), 462–477.
Francoeur, R.B. (2011). Interpreting interactions of ordinal or
continuous variables in moderated regression using the zero slope
comparison: tutorial, new extensions, and cancer symptom
applications.International Journal of Society Systems Science,
3(1/2), 137-158.
Cam
----------------------------------------
Date: Thu, 8 Dec 2011 18:57:29 +0100
Subject: Re: st: Presenting Interaction in LR
From: [email protected]
To: [email protected]
On Thu, Dec 8, 2011 at 6:25 PM, Campo, Marc wrote:
We are running a Linear Regression model where we are interested
in the effect of a dichotomous predictor (GROUP) on a ratio level
rehabilitation outcome scale. It is a pre/post situation where we
have adjusted for baseline values (BASELINE) of the scale. There
is an interaction between GROUP and BASELINE. People at the low
end of the scale do better in one group and at the higher end do
better in the other (but not much of a difference in clinical
terms).
I was going to present the coefficients for GROUP at varying
values of baseline. BASELINE however, is somewhat skewed and so
when I calculate the coefficient for group at the mean and 1SD
above and below the mean BASELINE value we end up with a lower
coefficient that is fairly close to the minimum value. Are there
other choices? 25, 50, 75Th percentiles? Graphs instead? I don't
think transforming BASELINE adds enough to be worth the complexity
and the relationship is fairly linear as is..
Quartiles sound fine to me, but the most important thing is that the
values make some substantive sense. There often are some values on a
scale that are especially meaningful, e.g. 12 and 16 years of
education in the American educational system (high school and college
degree). In that case I would use those values.
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/
*
* 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/