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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Skewness estimates with svyset data |

Date |
Wed, 5 Nov 2008 13:22:50 -0000 |

First, I think you need to keep explaining for the benefit of anyone trying to pick up on this thread that LMS refers to a method devised by [Timothy J.] Cole and others for handling growth curves. You earlier gave a reference that was just Cole et al. 2008. Despite a strong hint earlier from Stas Kolenikov, the further details of that reference are still outstanding. One of my dictionaries explains LMS as London Mathematical Society, London Missionary Society, and London, Midland and Scottish Railway. It is easy to guess that none of those apply but not so obvious that LMS here does _not_ mean Least Median of Squares as devised by Rousseeuw, as many statistically-minded people might imagine. Rousseeuw, P.J. 1984. Least median of squares regression. Journal, American Statistical Association 79: 871-880. The more general point, which should be obvious except that many list members act as if it were not true, is that the list includes people from several quite different disciplines. Hence if you want to maximise the readership of a question some explanations help a lot and rarely do harm. In terms of what you want to do: Several people on this list should know much, much more about Cole's method than I do but they are keeping quiet. I am surprised at the implication that you need to feed skewness to Cole's method. That is not, in particular, the case for -colelms- from SSC. I understood that Cole's method was in essence designed to work well with the possibly skew distributions that do occur and as such there is no specific need to prepare the data or satisfy the assumptions of the method, as there aren't any, except I guess that ages are accurate and size measurement error negligible. On the other hand, it may be that the missing reference, Cole et al. 2008, gives a quite different twist to the method, but then we are back to my earlier point. In general ignoring some fraction of data in the tail seems a very bad idea unless it is obvious that the values concerned are all untrustworthy. Even them some sensitivity analysis (with outliers vs without outliers) would seem advisable. Nick n.j.cox@durham.ac.uk Richard Palmer-Jones Yes, I have been planning to use LMS method - basically adding the adult parameters to the child hood ones given there. LMS needs skewness - hence my interest. I am only interested in the adults older that 25 (when both males and females have reached their full height) so complicated smoothing is not necessary. Yes, NHANES has heavy weighting which makes a considerable difference to estimates (and false PSUs). However, since the skewness reported by summarize is positive in adults I am wondering whether a simpler procedure is to truncate the parameter for valuies > 2.5sd, or to transform to logs, or some such and work in them. Unfortunately ln(weight) is also skewed. > Stas Kolenikov > > To Nick: yes, I've used skewness and kurtosis to test for normality a > bunch of times (and there's a famous Mardia's multivariate > generalization that I programmed up :)). But frankly I personally > don't remember seeing confidence intervals on skewness anywhere at > all. Estimation and testing are two related ways of looking at data > with statistics, but with skewness and kurtosis you really estimate > something to see that it is close enough to zero... and sometimes you > don't even estimate a thing and go straight to the test statistic. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Skewness estimates with svyset data***From:*"Richard Palmer-Jones" <richard.palmerjones@gmail.com>

**References**:**st: Skewness estimates with svyset data***From:*"Richard Palmer-Jones" <richard.palmerjones@gmail.com>

**Re: st: Skewness estimates with svyset data***From:*"Stas Kolenikov" <skolenik@gmail.com>

**RE: st: Skewness estimates with svyset data***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: Skewness estimates with svyset data***From:*"Richard Palmer-Jones" <richard.palmerjones@gmail.com>

**Re: st: Skewness estimates with svyset data***From:*"Stas Kolenikov" <skolenik@gmail.com>

**RE: st: Skewness estimates with svyset data***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: Skewness estimates with svyset data***From:*"Richard Palmer-Jones" <richard.palmerjones@gmail.com>

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