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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/ ----------------------------------------- ___________________________________________________________ Yahoo! Answers - Got a question? Someone out there knows the answer. Try it now. http://uk.answers.yahoo.com/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Testing normality of a continuous predictor variable in a logistic model***From:*Brendan <hsct@icon.co.za>

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