Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at

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

Re: st: Looking for courses in non-linear modelling and imputation techniques

From   Maarten Buis <>
Subject   Re: st: Looking for courses in non-linear modelling and imputation techniques
Date   Mon, 10 Oct 2011 18:54:56 +0200

On Mon, Oct 10, 2011 at 6:02 PM, Sofia Ramiro wrote:
> I want to explore non-linear relationships between outcomes that have so far
> been analyzed as if their relationship was linear. For this, I need to learn
> some statistical techniques to explore these relationships (besides normal
> regression, or even generalized estimation equations), if I am not wrong.
> This is more difficult to find in normal courses, at least the ones I have
> been finding, as they focus on linear relationships between variables...

This is actually routinely discussed in introductory regression
courses. The standard remedies depends on the discipline: either one
splits the linear variable up in categories and adds dummies/indicator
variables for those categories or one adds a square term. These
standard remedies tend to either trow away too much information
(dummies) or impose too much structure and thus not fit very well
(square term). Personally, I like adding linear splines (see: -help
mkspline-) as a nice compromise between adding a non-linear effect and
interpretable coefficients. Another option is fractional polynomials
(see: -help fracpoly- and Royston and Sauerbrei 2008).

Hope this helps,

Royston, P., and W. Sauerbrei. 2008. Multivariable Model-building: A
Pragmatic Approach to Regression Analysis
Based on Fractional Polynomials for Modelling Continuous Variables.
Chichester, UK: Wiley.

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
*   For searches and help try:

© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index