# Joris Meys

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bio website biomath.ugent.be/biomath/… location Ghent, Belgium age 36 member for 3 years, 3 months seen Nov 26 at 12:06 profile views 370

Statistician and R programmer at the faculty of Bio-Engineering, university of Ghent

Co-author of 'R for Dummies' (out in july 2012 )

contact : Joris - dot - Meys - at - Ugent - dot - be

# 318 Actions

 Nov26 revised How to calculate estimated proportions and their confidence intervals from a mixed model? edited title Nov26 answered How to calculate estimated proportions and their confidence intervals from a mixed model? Nov12 awarded Good Question Nov6 comment Is normality testing 'essentially useless'? @whuber You're free to update :) otherwise I'll update it when I find a bit more time. Cheers. Oct25 comment Is normality testing 'essentially useless'? Btw, QQ plots are not meant to detect such mixtures. They're graphical tools that give you a fair idea about whether or not you'll lose power an even get biased estimates when using specific tests. That's all there is to them. For 99% of the statistical questions in practical science, that's more than enough. Oct25 comment Is normality testing 'essentially useless'? Not one real life distribution is perfectly normal. So with large enough samples, all normality test should reject the null. So yes, SW does what it needs to do. But it is worthless for applied statistics. There's no point in going to eg a Wilcoxon when having a sample size of 5000 and an almost normal distribution. And that's what OP's remark was all about: does it make sense to test for normality when having large sample sizes? Answer: no. Why? because you detect (correctly) a deviation that doesn't matter for your analysis. As pointed out by the QQ plots Oct25 comment Is normality testing 'essentially useless'? That fact is true, but has no bearance with the CLT. The CLT is pretty specific about under what conditions the approximation holds. You throw different things on the same heap. Yes, Wilcox gives those examples. No, he isn't talking about large sample sizes or dismissing the CLT, far from even. He rightfully points out people forget about the conditions under which the CLT holds. I agree with you that testing differences with a sample size of 5000 doesn't make sense without stating what the minimal relevant difference is. But that's a whole other issue. Oct25 comment Is normality testing 'essentially useless'? @FrankHarrell I fail to see your point. Rand Wilcox was talking about sample sizes of 30 and more. The question is about very large samples. 30 isn't even large. 5000, that's large (and not that large actually). Doing the math Rand Wilcox did, the variance of the mean follows the chi-squared distribution pretty well for a sample of 5000, even when originating from a pretty skewed distribution. Oct25 comment Is normality testing 'essentially useless'? @whuber This answer addresses the question. The whole point of the question is the "near" in "near-normality". S-W tests what is the chance that the sample is drawn from a normal distribution. As the distributions I constructed are deliberately not normal, you'd expect the S-W test to do what it promises: reject the null. The whole point is that this rejection is meaningless in large samples, as the deviation from normality does not result in a loss of power there. So the test is correct, but meaningless, as shown by the QQplots Aug31 awarded Yearling Aug9 awarded Nice Answer Jul16 awarded Nice Answer Mar19 comment Is normality testing 'essentially useless'? @maximus with the function qqnormin R Mar12 awarded Popular Question Feb26 awarded Enlightened Feb26 awarded Nice Answer Feb22 comment Use coefficients of thin plate regression splines in a clustering method A very belated thank you! Dec12 comment Comparison of before and after ordinal data across two groups I don't agree on the test on the median. We're talking an ordinal scale here, and all tests on "median" are actually tests on location shift, which require distributions with the same shape. In an ordinal context, this is a rather dangerous assumption. Nov28 awarded Guru Oct8 comment Non negative lasso implementation in R Sorry for closing your question, but it is better asked and answered at www.crossvalidated.com I flagged the question for migration, so the mods will take care of it shortly. This said, please make your question clear and explain exactly what you want. The lasso expert in our research group couldn't possibly figure out what you were aiming at...