On 12 May 2008, at 09:29, Dieter Menne wrote:
Federico: First, mixed models are different from "standard 101 Anova", and quite a lot of the nesting stuff I used to ponder about 30 year ago when I started teaching this is no longer relevant and works implicitely when you code the parameters correctly.
with effect3 being random (all all the jazz that comes from this fact). I
fully apprecciate that the only reasonable F-tests would be for effect1, effect2 and effect1:effect2, but there is no way I can use lme to specify such simple thing without getting the *wrong* denDF. >> Good to know that you are sure what is "right"; probably == SAS. Since most people active in the lme-business have read http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests http://finzi.psych.upenn.edu/R/Rhelp02a/archive/76742.html carefully, you might be rather lonely.
I will. While I do, feel free to have a look at Appendix A.3 (page App6, at the end of the book) of the Zar 'Biostatistical Analysis', IV ed, second table from the top. That's where I get the feeling for what's right or wrong. I surely cannot get it from SAS because I never had it. I never had the budget for it, so much so I had to lear how to use R from the start because it was free and that was the budget of my department had for stats software All in all, if you feel statistical analysis has moved forth from such humble beginnings (the book I mean, not SAS), and you can convince of that every ref for every paper you submit, please do tell me how you do it, it would be more valuable than knowing how to fit my model. Cheers, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com