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...ocument which gives in detail the R code to do so for some given examples such as linear mixed effect models, survival analysis etc ... where the likelihood has a closed form and when it doesn't have a closed form ... I will then follow the same structure to fit my own model. Best wishes, Abderrahim [[alternative HTML version deleted]]

...0.513 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -3.122723638 -0.451811989 0.001009602 0.540504726 2.398619776 Number of Observations: 495 Number of Groups: 211 I think its a problem of local optimum...... Help!!!! Many thanks, Abderrahim Dr Abderrahim Oulhaj Oxford University Department of Pharmacology Mansfield Road Oxford OX1 3QT Tel: +44 1865 224098 Fax: +44 1865 224099 Email: abderrahim.oulhaj@pharmacology.oxford.ac.uk [[alternative HTML version deleted]]

...ction SSlogis of the "nlme" library allows the introduction of time varying covariates ? For example how can I interpret the xmid parameter (reperesenting the age at which we reach the half of the asymptote) if I want to explain it by a some time varying covariate? Thanks in adavance, Abderrahim Abderrahim Oulhaj, Phd in Statistics Oxford University Department of Pharmacology Mansfield Road Oxford OX1 3QT Tel: +44 1865 224098 Fax: +44 1865 224099 Email: abderrahim.oulhaj@pharmacology.oxford.ac.uk [[alternative HTML version deleted]]

Dear all, I am looking for an R package that fits multivariate gaussian or non-gaussian longitudinal outcomes. I am especially interested to non-gaussian outcomes since the outcomes I've got are discrete (some are binomial and some are count data). Many thanks in advance, Abderrahim [[alternative HTML version deleted]]

...binary data. Does the lmer do the work? The reason for asking that is: McCulloch (1997): "Unfortunately, PQL methods can perform poorly relative to Maximum likelihood" Agresti (2002) p. 524 "........but where possible we recommend using ML rather than PQL". Thanks a lot, Abderrahim [[alternative HTML version deleted]]

Dear All, I have the following error message when I fitted lmer to a binary data with the "AGQ" option: Error in family$mu.eta(eta) : NAs are not allowed in subscripted assignments In addition: Warning message: IRLS iterations for PQL did not converge Any help? Thanks in advance, Abderrahim [[alternative HTML version deleted]]

...I my case, the glmmPQL converges only and give good results when k is less than 3 (i.e. for a small number of random effects). I also used the gee (generalized estimating equations) to estimate the fixed effects and the same probleme ariseed with k. Is there any help? Thank you in advance, Abderrahim Oulhaj [[alternative HTML version deleted]]

Hi, I am looking for any procedure in R to fit "Latent variables models" in particular "Latent trait models (i.e. for binary data)". could anyone help me? Many thanks , Dr Abderrahim Oulhaj Oxford University Department of Pharmacology Mansfield Road Oxford OX1 3QT Tel: +44 1865 224098 Fax: +44 1865 224099 Email: abderrahim.oulhaj@pharmacology.oxford.ac.uk [[alternative HTML version deleted]]

...surv.coxph <- summary(survfit(fit.coxph))[[1]] The finite-dimension parameters theta in fit.nltm and fit.coxph are similar but as you can see "surv.nltm" and "surv.coxph" are completey different. Furthermore, "fit.nltm" have all values close to 1. All the bests Abderrahim [[alternative HTML version deleted]]

...surv.coxph <- summary(survfit(fit.coxph))[[1]] The finite-dimension parameters theta in fit.nltm and fit.coxph are similar but as you can see "surv.nltm" and "surv.coxph" are completey different. Furthermore, "fit.nltm" have all values close to 1. All the bests Abderrahim [[alternative HTML version deleted]]

Dear All, I wonder if there is an R package to estimate the generalized linear mixed models but with a random effects having a mixture of normals as a prior distributinon .. Thank you, Abderrahim [[alternative HTML version deleted]]