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st: test for departure from linearity


From   "Raoul C Reulen" <r.c.reulen@bham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: test for departure from linearity
Date   Fri, 18 Nov 2005 11:15:10 -0000

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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