search for: mixedmodels

Dear All, This may sound like a dumb question but I am trying to use a mixed model to determine the predictors of bat activity along hedges within 8 sites. So my response is continuous (bat passes) my predictors fixed effects are continuous (height metres), width (metres) etc and the random effect is site - can you tell me if the fixed effects can be continuous as all the examples I have

...tistical Software" (forthcoming, CRC Press). Participants will interact with Dr. Galecki via a private discussion board; the course will require about 5-15 hours per week and there are no set hours when you must be online. Registration and details at http://www.statistics.com/content/courses/mixedmodels/index.html Peter Bruce courses at statistics.com

Hi, I am Olga Viedma. I am running a Zero-inflated negative binomial (ZINB) multi-level model using MCMCglmm package. I have a doubt. Can I use the "Liab" outputs as fitted data, instead of the predicted values from "predict"? The liab outputs fit very well with the observed data, whereas the predicted values are so bad. Thanks in advance, Olga Viedma D . Olga

Hello R-help, I'm studying an example in the R book.? The data file is available from the link below.http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/fertilizer.txt Could you explain Why the results from lme() and lmer() are different in the following case? In other examples, I can get the same results using the two functions, but not here...? Thank you.Miya library(lme4)library(nlme)#

Hello, I am working from a linux 64 machine on a server with R-2.12 (I can't update to 2.13). I am iterating through many linear mixed models for longitudinal data and I occasionally receive the following convergence error: > BI.lme <- lme(cd4 ~ time + genBI + genBI:time + C1 + C2 + C11 + C12, random =~ 1 + time | IID, data = d) Error in lme.formula(cd4 ~ time + genBI + genBI:time +

...1. Nested model comparison (likelihood-ratio test) with either the anova() function or drop1(model,test='Chisq') 2. use the p-values from the ANOVA results (see Pinheiro and Bates 2000, pp. 90-91, for some notes on which test is preferred as well as the GLMM FAQ: https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html) But please please note that it would be misleading to say that these are the p-values for the coefficients in your model. These issues are the same for both mixed and 'normal' regression models. Phillip On 30/11/17 16:56, Akihiro Koyama wrote: > Hi Phillip, > &g...

Hi, I just came across the following issue regarding mixed effects models: In a longitudinal study individuals (variable ind) are observed for some response variable. One explanatory variable, f, entering the model as fixed effect, is a (2-level) factor. The expression of that factor is constant for each individual across time (say, the sex of the individual). ind enters the model as grouping