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


From   Brendan <hsct@icon.co.za>
To   Stata List <statalist@hsphsun2.harvard.edu>
Subject   st: Testing normality of a continuous predictor variable in a logistic model
Date   Tue, 27 Nov 2007 13:04:49 +0200

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?
Regards
Brendan
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