Raoul,
It sounds like you are interested in a RESET test. This is sometimes,
rather misleadingly, called an omitted variables test, but it's better
thought of as a test for neglected nonlinearities in functional form.
Stata has a canned RESET test called -ovtest-. -ivreset- (downloadable
from ssc-archives) will also work after -regress- and gives you more
options.
Hope this helps.
Cheers,
Mark
> Dear Statalisters,
>
> What is the best way to test for a departure from linearity in a
> regression model? Graphically or statistically? I ask this because when I
> use, for example graphical methods like: .lincheck or .cprplot (component
> plus residual plot), or .acprplot(augmented component plus residual) the
> variable that I test (age) looks very linear. However, when I do a
> statistical test for it, it is not linear!
> I first create a regression model with a dummy variable(i.age) and then
> compare it to a regression model with the same
> variable but then as an ordinal variable (age). See below for an example
> (BP=blood pressure)
>
> xi: regress BP i.age
> estimate store Model1
> regress BP age
> estimate store Model2
> lrtest M2 M2
>
> My sample size is very large (approx 20,000 subjects), could this be why
> the test gives a significant result while the plots look very linear?
>
> Thanks
>
> Raoul
>
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>
Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3294
email: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
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