similar to: confidence interval too small in nlme?

Dear R-help list members I gathered longitudinal data on fish behaviour which I try to analyse using a multi level model for change. Mostly, I am following Singer & Willett (2003), who provide also the S/R code for their examples in the book (e.g. http://www.ats.ucla.edu/stat/Splus/examples/alda/ch4.htm). Of course I am interested in change over time, but I am also very much interested in

Hello- I understand that it's convention, when comparing two models using the anova function anova(model1, model2), to put the more "complicated" (for want of a better word) model as the second model. However, I'm using lme in the nlme package and I've found that the order of the models actually gives opposite results. I'm not sure if this is supposed to be the case

Hello! One note/question hier about specification of control-parameters in the lme(...,control=list(...)) function call: i tried to specify tne number of iteration needed via lme(....,control=list(maxIter=..., niterEM=...,msVerbose=TRUE)) but every time i change the defualt values maxIter (e.g. maxIter=1, niterEM=0) on ones specified by me, the call returns all the iterations needed until

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

Dear List, While trying to define a customised CITATION file for a package, following R-exts, I realised that if I use only one 'citEntry' I got both a text description and a BibTex entry for the package, as for the 'nlme' package: -------------------------- citation('nlme') To cite package 'nlme' in publications use: Jose Pinheiro, Douglas Bates, Saikat

Dear list, i am a student of psychology and have to do a multilevelanalysis on some data. About that i have one general and one specific question. This is what i have copied from the help-file on lme: data(bdf) fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR) summary(fm) after summary(fm) i get the following error:

Is there some fast (built-in?) way to get the OR of all the elements in a logical vector? In other words, is there some fast (built-in) version of the function vor below? Thanks. -Ben vor <- function(v) { ans <- v[1] if (length(v) > 1) for (i in 2:length(v)) ans <- ans | v[i] ans }

Dear all, Edmond Ng (http://multilevel.ioe.ac.uk/softrev/reviewsplus.pdf) provides an example to fit the mixed effects meta-analysis in Splus 6.2. The syntax is: lme(fixed=d~wks, data=meta, random=~1|study, weights=varFixed(~Vofd), control=lmeControl(sigma=1)) where d is the effect size, study is the study number, Vofd is the variance of the effect size and meta is the data frame.

Dear all, Given a LME model (following the notation of Pinheiro and Bates 2000) y_i = X_i*beta + Z_i*b_i + e_i, is it possible to extract the variance-covariance matrix for the estimated beta_i hat and b_i hat from the lme fitted object? The reason for needing this is because I want to have interval prediction on the predicted values (at level = 0:1). The "predict.lme" seems to

I can ask my question using and example from Chapter 1 of Pinheiro & Bates. > # 1.4 An Analysis of Covariance Model > > OrthoFem <- Orthodont[ Orthodont$Sex == "Female", ] > fm1OrthF <- + lme( distance ~ age, data = OrthoFem, random = ~ 1 | Subject ) > summary( fm1OrthF ) Linear mixed-effects model fit by REML Data: OrthoFem AIC BIC

Greetings, 1) Is there a nice way of extracting the variance estimates from an lme fit? They don't seem to be part of the lme object. 2) In a series of simulations, I am finding that with ML fitting one of my random effect variances is sometimes being estimated as essentially zero with massive CI instead of the finite value it should have, whilst using REML I get the expected value. I guess

Dear All, Using:- R : Copyright 2005, The R Foundation for Statistical Computing Version 2.1.1 (2005-06-20), ISBN 3-900051-07-0 and Jose Pinheiro, Douglas Bates, Saikat DebRoy and Deepayan Sarkar (2005). nlme: Linear and nonlinear mixed effects models. R package version 3.1-65. on a WINDOWS 2000 machine I am trying to run the scripts from the Mixed Models book and am running into some

Dear friends, regression towards the mean is interesting in medical circles, and a very recent paper (The American Statistician November 2007;61:302-307 by Krause and Pinheiro) treats it at length. An initial example specifies (p 303): "Consider the following example: we draw 100 samples from a bivariate Normal distribution with X0~N(0,1), X1~N(0,1) and cov(X0,X1)=0.7, We then calculate

Dear R users, I am writing to you because I have a few question on how to fix the error term variances in lme in the hope that you could help me. To my knowledge, the closest possibility is to fix the var-cov structure, but not the whole var-cov matrix. I found an old thread (a few years ago) about this, and it seems that the only alternative is to write the likelihood down and use optim or a

Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

Some time ago I tried to find out how to compute remainders in R. I now know that it is done with %%, which is documented in help('+'), but before someone told me that I tried: help('remainder'), help.search('remainder'), apropos('remainder') help('modulo'), help.search('modulo'), and apropos('modulo') all of which yielded nothing. I then

Dear all, I try to load the nlme library for Linear and nonlinear mixed effects models by Jose Pinheiro, Douglas Bates and Saikat DebRoy but I get the following error message: > library(nls) > library(nlme) Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library "C:\Program\R\rw1010/library/nlme/libs/nlme.dll": LoadLibrary failure: Det

Could someone identify a function that I might use to perform a components of variance analysis? In addition to the variance attributable to each factor, I would also like to obtain the SE of the variances. Thank you, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of

Hi R users! I will try to state my question again. I have longitudinal data and fitted the following model with lme: Y = X*beta + U + W(t) + Z where U ~ N(0, nu*I) I is the identity matrix, so this is the random intercept W(t)~ N(0, sigma*H) and H is a matrix which incorporates a Gaussian serial correlation (covariance) in the offdiagonal

Hi All, does anyone know if the package GLME by J. Pinheiro is available anywhere in any form? checking on the archive I got that it was at some point, as as a beta version (for S-Plus only, alas)... Cheers, Federico ========================= Federico C.F. Calboli Department of Biology University College London Room 327 Darwin Building Gower Street London WClE 6BT Tel: (+44) 020 7679 4395