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Re: st: Testing normality of a continuous predictor variable in a logistic model


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Testing normality of a continuous predictor variable in a logistic model
Date   Tue, 27 Nov 2007 11:31:23 +0000 (GMT)

--- Brendan <hsct@icon.co.za> wrote:
> I am working with a dataset containing 30000 observations. Some of  
> the explanatory variables are continuous. If I perform usual tests  
> for normality the numbers are too great for swilk or for sfrancia,  
> and if I use sktest the result is "absurdly" large values and rejects
> the hypothesis of normal distribution. The frequency histogram,  
> cumulative frequency plot and normal plot all look normal with no  
> outliers. I presume that with such large numbers even very small  
> deviations from normal will lead to a significant result. The box- 
> tidwell test indicates that the model relationship is linear for all 
> these continuous variables. Is it safe to ignore the sktest results?

An explanatory variable can have a linear or non-linear effect on the
log odds when it is non-normally distributed and a linear or non-linear
effect on the log odds when it is normally distributed. Normality of
the explanatory variable has nothing to do with whether or not it has a
linear effect. So the test were irrelevant for your purpose to begin
with. 

-- 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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