Re: [R] Mixed effect model in R
Thanks for the helping links. Now, I worked out that I have to use the lme4 package (with the lmer function) for my analysis. But now I do not understand the input to the lmer function. In the lme function (of the nlme package) the correct input would in my case be: lme(fixed=Ac_LC~cond_ind,random=~img_cond|sub_ind/cond_ind) but also after reading the help and the R news I do not understand the formula I have to use for the lmer function. Could someone help me translating the lme input to a lmer input? And does someone know of a good explanation of the kinds of formulas you can input? In the books they only explain the lme input. Thanks, Lina 2006/10/17, Stefan Grosse [EMAIL PROTECTED]: Please always reply to the list as well as there always might be someone faster/better answering (or it could be that I am wrong, so someone might correct me) Indeed Pinheiro/Bates assume gaussian error terms... but I am not really sure whether you meant that with non normally distributed respond variable resp. with non-normal data however: / Mixed-effects models: / The recommended nlme http://cran.r-project.org/src/contrib/Descriptions/nlme.html package, associated with Pinheiro and Bates, / Mixed-Effects Models in S and S-PLUS / (Springer, 2000), fits linear and nonlinear mixed-effects models, commonly used in the social sciences for hierarchical and longitudinal data. Generalized linear mixed-effects models may be fit by the glmmPQL function in the MASS package, and by the lmer function in the Matrix http://cran.r-project.org/src/contrib/Descriptions/Matrix.html package (related to the lme4 http://cran.r-project.org/src/contrib/Descriptions/lme4.html package, which largely supersedes nlme http://cran.r-project.org/src/contrib/Descriptions/nlme.html for / linear / mixed models). Also see the lmeSplines http://cran.r-project.org/src/contrib/Descriptions/lmeSplines.html and lmm http://cran.r-project.org/src/contrib/Descriptions/lmm.html packages. [ http://cran.r-project.org/src/contrib/Views/SocialSciences.html ] Lina Jansen schrieb: 2006/10/17, Stefan Grosse [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]: Interesting packages for you might be the nlme and lme4 packages and as a book Pinheiro/Bates, Mixed-Effects Models in S and S-Plus Thank you for the answer. I am always unsure concerning the non-normality. Can I use the nlme and lme4 with non-normal data? First, I thought they would work like an ANOVA but with random and fixed effects. [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Mixed effect model in R
Hi, I am analysing an experiment that has one fixed (6 conditions) and two random factors (11 subjects, 24 images in the conditions). I read somewhere else that you can also see such a design as a nested experiment with the hierarchy: subjects - condition - image. For some analysis I have one respond variable and for others I have more. The response variables are non-normally distributed. Now the question: Is there a package that can deal with such a design? I would like to use a generalized linear model. Are there glms that are extended to do multivariate analysis (for the 2 random + 1 fixed variable design)? And how do you call such a design? Last question: Can you suggest me some literature about such a problem? I am quite unsure concerning the analysis. Thanks for any advice lisra [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Mixed effect model in R
Interesting packages for you might be the nlme and lme4 packages and as a book Pinheiro/Bates, Mixed-Effects Models in S and S-Plus Lina Jansen schrieb: Hi, I am analysing an experiment that has one fixed (6 conditions) and two random factors (11 subjects, 24 images in the conditions). I read somewhere else that you can also see such a design as a nested experiment with the hierarchy: subjects - condition - image. For some analysis I have one respond variable and for others I have more. The response variables are non-normally distributed. Now the question: Is there a package that can deal with such a design? I would like to use a generalized linear model. Are there glms that are extended to do multivariate analysis (for the 2 random + 1 fixed variable design)? And how do you call such a design? Last question: Can you suggest me some literature about such a problem? I am quite unsure concerning the analysis. Thanks for any advice lisra [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Mixed effect model in R
Please always reply to the list as well as there always might be someone faster/better answering (or it could be that I am wrong, so someone might correct me) Indeed Pinheiro/Bates assume gaussian error terms... but I am not really sure whether you meant that with non normally distributed respond variable resp. with non-normal data however: / Mixed-effects models: / The recommended nlme http://cran.r-project.org/src/contrib/Descriptions/nlme.html package, associated with Pinheiro and Bates, / Mixed-Effects Models in S and S-PLUS / (Springer, 2000), fits linear and nonlinear mixed-effects models, commonly used in the social sciences for hierarchical and longitudinal data. Generalized linear mixed-effects models may be fit by the glmmPQL function in the MASS package, and by the lmer function in the Matrix http://cran.r-project.org/src/contrib/Descriptions/Matrix.html package (related to the lme4 http://cran.r-project.org/src/contrib/Descriptions/lme4.html package, which largely supersedes nlme http://cran.r-project.org/src/contrib/Descriptions/nlme.html for / linear / mixed models). Also see the lmeSplines http://cran.r-project.org/src/contrib/Descriptions/lmeSplines.html and lmm http://cran.r-project.org/src/contrib/Descriptions/lmm.html packages. [ http://cran.r-project.org/src/contrib/Views/SocialSciences.html ] Lina Jansen schrieb: 2006/10/17, Stefan Grosse [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]: Interesting packages for you might be the nlme and lme4 packages and as a book Pinheiro/Bates, Mixed-Effects Models in S and S-Plus Thank you for the answer. I am always unsure concerning the non-normality. Can I use the nlme and lme4 with non-normal data? First, I thought they would work like an ANOVA but with random and fixed effects. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
