Default P-values goodness-of-fit tests

[lheer]

Hi everyone,

I want to run some Goodness-of-fit tests for several variables, but for every variable the three tests (KS, AD and C-vM) show similar p-values 0.010, 0.005, 0.005 respectively. This would mean that every variable is not normally distributed. However, when looking at Q-Q plot and histograms, not every variable is not normally distributed.

It looks like these p-values are default p-values, since for every variable these p-values are the same.

This is what I did:

proc univariate data=<library.dataset>;
var <variables>;
histogram /normal;
qqplot;
run;

Can anyone help me?

Thank you!

[PaigeMiller]

Show us what you are seeing.

[lheer]

I see these p-values for every single variable, but with different D-, W-Sq- and A-Sq-values.

[ballardw]

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@lheer wrote:

I see these p-values for every single variable, but with different D-, W-Sq- and A-Sq-values.

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Send the output to a data set and you can examine the, almost certainly miniscule, actul p-values. The TABLES the procedure reports with will use a threshold value instead of attempting to fit a value like 0.00000000004583 into a 6-column display.

[Ksharp · Accepted solution]

@Rick_SAS  wrote many blogs about this GOF .especially your data is not big enough or have some integer value .

These tests (KS, AD and C-vM) are not always trusted  . 

I would follow Q-Q plot .

[Rick_SAS]

I'm going to guess that you are testing large data? As KSharb suggests, you might want to read the article "Goodness-of-fit tests: A cautionary tale for large and small samples".

Anyway, a more important question is WHY you want to test many variables for normality. What are you trying to accomplish? Why does a lack of normality bother you?

[Ksharp]

@Rick_SAS  You are right. OP must have a big table .

[PaigeMiller]

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@lheer wrote:

... but for every variable the three tests (KS, AD and C-vM) show similar p-values 0.010, 0.005, 0.005 respectively

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This is NOT what the SAS output is showing. It does not show a value of 0.010 or 0.005 or 0.005 respectively.

It shows a value of <0.010 and <0.005 and <0.005, and these are not default values, these are calculations, rounded to some meaningful threshold.