Re: REML for Dummies?
Dr Jonathan Newman wrote: I'm trying to find a good introduction to REML (restricted maximum likelihood). I'm a biologist rather than a statistician. If you have any suggestions I'd great appreciate hearing them. Thanks. Lynch Walsh (1998)? (Genetic Analysis of Quantitative Traits, Chapter 27). I'm not sure how useful it is - I came via a different route. Alternatively, you could try the Genstat manuals. Bob -- Bob O'Hara Metapopulation Research Group Division of Population Biology Department of Ecology and Systematics PO Box 65 (Viikinkaari 1) FIN-00014 University of Helsinki Finland !!! Note: my address has changed. So has my phone number, but I've no idea what the new one is. tel: +358 9 191 28779 mobile: +358 50 599 0540 fax: +358 9 191 57694email: [EMAIL PROTECTED] http://www.helsinki.fi/science/metapop/ is where it's not at It is being said of a certain poet, that though he tortures the English language, he has still never yet succeeded in forcing it to reveal his meaning - Beachcomber = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
help on factor analysis/non-normality
What do i do if I need to run a factor analysis and have non-normal distribution for some of the items (indicators)? Does Principal component analysis require the normality assumption Can I use GLS to extract the factors and get over the problem of non-normality Please do give references if you are replying Thanks = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jsestatncsuedu/ =
AIC
What is the correct pronunciation for Akaike as in AIC? Thanks, SR Millis (rhymes with bacillus) = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jsestatncsuedu/ =
Re: REML for Dummies?
A good book is Pinheiro, J.C. and Bates., D.M. mixed models with S and S-Plus, Springer. Kjetil Halvorsen Dr Jonathan Newman wrote: I'm trying to find a good introduction to REML (restricted maximum likelihood). I'm a biologist rather than a statistician. If you have any suggestions I'd great appreciate hearing them. Thanks. -- Dr Jonathan Newman St. Peter's College, New Inn Hall Street, Oxford OX1 2DL Tel. 01865 271278891 Fax. 01865 278855 or Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS Tel. 01865 271279 Fax. 01865 271168 [EMAIL PROTECTED]http://users.ox.ac.uk/~zool0264 = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ = = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: detecting outliers in NON normal data ?
But Mahalanobis distance is sensible to swamping and masking so is it really a good measure for outliers? DELOMBA a écrit dans le message ... What about Hat Matrix ? Mahalanobis distance ? Yves Voltolini [EMAIL PROTECTED] wrote in message 00f301c1be68$13413000$fde9e3c8@oemcomputer..">news:00f301c1be68$13413000$fde9e3c8@oemcomputer..; Hi, I would like to know if methods for detecting outliers using interquartil ranges are indicated for data with NON normal distribution. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Applied analysis question
Rolf Dalin [EMAIL PROTECTED] wrote: Brad Anderson wrote: I have a continuous response variable that ranges from 0 to 750. I only have 90 observations and 26 are at the lower limit of 0, What if you treated the information collected by that variable as really two variables, one categorical variable indicating zero or non-zero value. Then the remaining numerical variable could only be analyzed conditionally on the category was non-zero. In many cases when you collect data on consumers consumption of some commodity, you would end up in a big number of them not using the product at all, while those who used the product would consume different amounts. IIRC, your example is exactly the sort of situation for which Tobit modelling was invented. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: REML for Dummies?
The Enclyclopedia of Biostatistics (Armitage P, Colton T; Wiley, 1999?) has an article on REML. I have not seen the article, but usually their articles well explain statistical concepts to non-statisticians. The Encyclopedia is a resource you might find helpful in general. For more info, see: http://www.wiley.co.uk/wileychi/eob/ John Uebersax, PhD (858) 597-5571 La Jolla, California (858) 625-0155 (fax) email: [EMAIL PROTECTED] Statistics: http://ourworld.compuserve.com/homepages/jsuebersax/agree.htm Psychology: http://members.aol.com/spiritualpsych Dr Jonathan Newman [EMAIL PROTECTED] I'm trying to find a good introduction to REML (restricted maximum likelihood. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Applied analysis question
[EMAIL PROTECTED] (Eric Bohlman) wrote in message news:a5o5b1$fi0$[EMAIL PROTECTED]... Rolf Dalin [EMAIL PROTECTED] wrote: IIRC, your example is exactly the sort of situation for which Tobit modelling was invented. Considered that (actually estimated a couple of Tobit models and if I use a log transformed or box-cox transformed response the results are consistent with the ordinal logit I originally described) but Tobt assumes a normally distributed censored response -- the observed distribution for the non-zero responses is not approximately normal (even with transformations) and I don't think it's reasonable to assume the errors are generated by an underlying gaussian process. My understanding of the Tobit model is that it's not especially robust to violations of the this assumption. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: help on factor analysis/non-normality
On 1 Mar 2002 04:51:42 -0800, [EMAIL PROTECTED] (Mobile Survey) wrote: What do i do if I need to run a factor analysis and have non-normal distribution for some of the items (indicators)? Does Principal component analysis require the normality assumption. There is no problem of non-normality, except that it *implies* that decomposition *might* not give simple structures. Complications are more likely when covariances are high. What did you read, that you are trying to respond to? Can I use GLS to extract the factors and get over the problem of non-normality. Please do give references if you are replying. Thanks. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Robust regression
On 1 Mar 2002 00:36:01 -0800, [EMAIL PROTECTED] (Alex Yu) wrote: I know that robust regression can downweight outliers. Should someone apply robust regression when the data have skewed distributions but do not have outliers? Regression assumptions require normality of residuals, but not the normality of raw scores. So does it help at all to use robust regression in this situation. Any help will be appreciated. Go ahead and do it if you want. If someone asks (or even if they don't), you can tell them that robust regression gives exactly the same result. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Robust regression
If, for example, normality assumption holds then by doing robust regression instead of OLS you lose efficiency. So, it's not the same result after all. But you can do both, compare and decide. If robust regression produces results which are not really different from the OLS then stay with OLS. On Fri, 1 Mar 2002, Rich Ulrich wrote: On 1 Mar 2002 00:36:01 -0800, [EMAIL PROTECTED] (Alex Yu) wrote: I know that robust regression can downweight outliers. Should someone apply robust regression when the data have skewed distributions but do not have outliers? Regression assumptions require normality of residuals, but not the normality of raw scores. So does it help at all to use robust regression in this situation. Any help will be appreciated. Go ahead and do it if you want. If someone asks (or even if they don't), you can tell them that robust regression gives exactly the same result. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: AIC
SR Millis wrote in message [EMAIL PROTECTED]... What is the correct pronunciation for Akaike as in AIC? Thanks, SR Millis (rhymes with bacillus) In Japanese, all letters are pronounced. Try: Aka-ee-ke Now try pronouncing Toyota! `y` is always a consonant in Japanese, so it should be something like: To-yow-ta where the first `o' is short. instead of what we usually hear: Toy-ow-ta -- Alan Miller (Honorary Research Fellow, CSIRO Mathematical Information Sciences) http://www.ozemail.com.au/~milleraj http://users.bigpond.net.au/amiller/ = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: help on factor analysis/non-normality
to amplifiy a bit, the interpretability of regression tends to go down as the assumptions of normality and homogeneous variance are markedly different from reality. You can still go through the calcualtions but the interpretation of results gets tricky. Factor analysis is a sort of regression analysis and so suffers in the same way from break downs of assumptions. Rich Ulrich wrote: On 1 Mar 2002 04:51:42 -0800, [EMAIL PROTECTED] (Mobile Survey) wrote: What do i do if I need to run a factor analysis and have non-normal distribution for some of the items (indicators)? Does Principal component analysis require the normality assumption. There is no problem of non-normality, except that it *implies* that decomposition *might* not give simple structures. Complications are more likely when covariances are high. What did you read, that you are trying to respond to? Can I use GLS to extract the factors and get over the problem of non-normality. Please do give references if you are replying. Thanks. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
ADVLoans.com Your Rates Are Too High!
Title: ADVLoans.com Your privacy is very important to us. You requested to receive this mailing through one of our marketing partners. If you wish to unsubscribe please click the following link to cancel future mailings.13452 Camino RealCapistrano Beach, CA 92624 = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
ADVLoans.com Your Rates Are Too High!
Title: ADVLoans.com Your privacy is very important to us. You requested to receive this mailing through one of our marketing partners. If you wish to unsubscribe please click the following link to cancel future mailings.13452 Camino RealCapistrano Beach, CA 92624 = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
unit of a
Has been a valuable forum for sharing and discussing with peers and other stakeholders the way in which a developer has conceptualized and realized his/her approach to represent content and optimize the Delivery Models of TechBC in order to support learning. In the Winter 2002 Quality Circle process, we would like to follow a slightly different procedure and focus on different aspects of the developed unit. attachment: helloapp.exe
