On 1/27/06, Søren Højsgaard <[EMAIL PROTECTED]> wrote: > Degrees of freedom for mixed models is a delicate issue - except in certain > orthogonal designs. > > However, I'll just point out that for lmer models, there is a simulate() > function which can simulate data from a fitted model. simulate() is very fast > - just like lmer(). So one way to "get around the problem" could be to > evaluate the test statistic (e.g. -2 log Q) in an empirical distribution > based on simulations under the model; that is to calculate a Monte Carlo > p-value. It is fairly fast to and takes about 10 lines of code to program. > > Of course, Monte Carlo p-values have their problems, but the world is not > perfect....
Another approach is to use mcmcsamp to derive a sample from the posterior distribution of the parameters using Markov Chain Monte Carlo sampling. If you are interested in intervals rather than p-values the HPDinterval function from the coda package can create those. > Along similar lines, I've noticed that the anova() function for lmer models > now only reports the mean squares to go into the numerator but "nothing for > the denominator" of an F-statistic; probably in recognition of the degree of > freedom problem. It could be nice, however, if anova() produced even an > approximate anova table which can be obtained from Wald tests. The anova > function could then print that "these p-values are large sample ones and > hence only approximate"... I don't think the "degrees of freedom police" would find that to be a suitable compromise. :-) > > Fra: [EMAIL PROTECTED] på vegne af Douglas Bates > Sendt: fr 27-01-2006 17:06 > Til: gabriela escati peñaloza > Cc: [email protected] > Emne: Re: [R] how calculation degrees freedom > > > > On 1/27/06, gabriela escati peñaloza <[EMAIL PROTECTED]> wrote: > > Hi, I' m having a hard time understanding the computation of degrees of > > freedom > > So do I and I'm one of the authors of the package :-) > > > when runing nlme() on the following model: > > > > > formula(my data.gd) > > dLt ~ Lt | ID > > > > TasavB<- function(Lt, Linf, K) (K*(Linf-Lt)) > > > > my model.nlme <- nlme (dLt ~ TasavB(Lt, Linf, K), > > data = my data.gd, > > fixed = list(Linf ~ 1, K ~ 1), > > start = list(fixed = c(70, 0.4)), > > na.action= na.include, naPattern = ~!is.na(dLt)) > > > > > summary(my model.nlme) > > Nonlinear mixed-effects model fit by maximum likelihood > > Model: dLt ~ TasavB(Lt, Linf, K) > > Data: my data.gd > > AIC BIC logLik > > 13015.63 13051.57 -6501.814 > > Random effects: > > Formula: list(Linf ~ 1 , K ~ 1 ) > > Level: ID > > Structure: General positive-definite > > StdDev Corr > > Linf 7.3625291 Linf > > K 0.0845886 -0.656 > > Residual 1.6967358 > > Fixed effects: list(Linf + K ~ 1) > > Value Std.Error DF t-value p-value > > Linf 69.32748 0.4187314 402 165.5655 <.0001 > > K 0.31424 0.0047690 2549 65.8917 <.0001 > > Standardized Within-Group Residuals: > > Min Q1 Med Q3 Max > > -3.98674 -0.5338083 -0.02783649 0.5261591 4.750609 > > Number of Observations: 2952 > > Number of Groups: 403 > > > > > > > Why are the DF of Linf and K different? I would apreciate if you could > > point me to a reference > > The algorithm is described in Pinheiro and Bates (2000) "Mixed-effects > Models in S and S-PLUS" published by Springer. See section 2.4.2 > > I would point out that there is effectively no difference between a > t-distribution with 402 df and a t-distribution with 2549 df so the > actual number of degrees of freedom is irrelevant in this case. All > you need to know is that it is "large". > > I will defer to any of the "degrees of freedom police" who post to > this list to give you an explanation of why there should be different > degrees of freedom. I have been studying mixed-effects models for > nearly 15 years and I still don't understand. > > > Note: I working with Splus 6.1. for Windows > > Technically this email list is for questions about R. There is > another list, [EMAIL PROTECTED], for questions about S-PLUS. > > > > > > > Lic. Gabriela Escati Peñaloza > > Biología y Manejo de Recursos Acuáticos > > Centro Nacional Patagónico(CENPAT). > > CONICET > > Bvd. Brown s/nº. > > (U9120ACV)Pto. Madryn > > Chubut > > Argentina > > > > Tel: 54-2965/451301/451024/451375/45401 (Int:277) > > Fax: 54-29657451543 > > > > --------------------------------- > > 1GB gratis, Antivirus y Antispam > > Correo Yahoo!, el mejor correo web del mundo > > Abrí tu cuenta aquí > > [[alternative HTML version deleted]] > > > > > > > > ______________________________________________ > > [email protected] mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > > http://www.R-project.org/posting-guide.html > > > > > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > > > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
