If you transform the independent variable you are changing the shape of
the relation between your depedent and independent variable. You can
see some examples of such shapes by using the -twoway function- graphs.
For instance, you asked about the log transformed x. You can see such a
shape by typing:
twoway function y = .1*ln(x), range(0 10)
You will see that a unit increase in x has a different impact depending
on where you start. A unit increase in x when you start from x=.5 has a
much bigger impact on y than when you start from x=8.
Fox (1991) has a nice introduction on this issue in term of linear
regression.
-- Maarten
John Fox (1991) Regression Diagnostics: An Introduction. Thoasand Oaks:
Sage.
--- Mohammed El Faramawi <[email protected]> wrote:
> Hi Marteen,
> You wrote Anyhow the real issue with transforming the
> independent variables is whether the effect is linear,
> or gradually slowing down (log) u-shaped, quadratic,
> etc.' would you mind explaining more? especially what
> do you mean by slowing down and (log)
> Thank you .
> --- Maarten buis <[email protected]> wrote:
>
> > The independent variables don't need to be normally
> > distributed. If you
> > log transfom the variable than you think that if you
> > start with a small
> > dose, an increase has a much bigger effect than when
> > you start with a
> > larger, which may or may not make sense. Anyhow the
> > real issue with
> > transforming the indepedent variables is whether the
> > effect is linear,
> > or gradually slowing down (log) u-shaped, quadratic,
> > etc. As an aside,
> > if you compute percentile rank scores, you won't
> > make that variable
> > normal, uniformly distributed.
> >
> > -- Maarten
> >
> > --- Mohammed El Faramawi <[email protected]> wrote:
> > > I have questions about the independent variable
> > > transformation.
> > > I have an independent variable (lead mg/dl) which
> > is
> > > not normally distributed. I am trying to run it in
> > a
> > > cox hazard model the out come is mortality. What
> > > should I do with lead
> > > 1) Should I log transform it? I did that but it is
> > > still not normally ditributed after transformatin.
> > > 2) Leave it as it is because transformation does
> > not
> > > change the distribution?
> > > 3) categorize using quartiles or percentiles?
> >
> >
> > -----------------------------------------
> > 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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>
>
>
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-----------------------------------------
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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