--- Alex Asiimwe <[email protected]> wrote:
> Assuming I have age and gender, then I transform age to age*age to
> normalise it. From here, I want logistic regression model to predit
> an outcome- lets say mortality. Will I be wrong to use age, age*age
> and gender all at the same time in the model? If so, what are the
> implications? e.g logistic outcome age age*age gender; In otherwords
> is acceptable to use a variable and its transform in MLR (step wise)?
There is no problem to add age and age squared (age*age) to the same
model. What it means is that you think that the effect of age on the
log odds is non-linear, which in many cases is plausible especialy if
your age variable covers a large range.
However:
- I would not call age*age normalizing
- there are many other ways of allowing for non-linear effects, e.g.
splines, see -help mkspline-, or fractional polynomials, see
-help fracpoly-.
- stepwise is not acceptable, see:
http://www.stata.com/support/faqs/stat/stepwise.html
-- Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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