[R] Checking for linearity by ploting residuals against predicted values (lme)?
Hello, Is there a easy way to get p-values when testing linearity of a model by ploting residuals against predicted values? Regards Kes, [[alternative HTML version deleted]] __ R-help@r-project.org 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] How to calculate normality of the residuals from a test in R?
Hi, How do I calculate normality distribution of the residuals from a test in R? I have tried plot(mod1), and I get a nice plot, but no p-value... is there some other ways to calculate this? Regards Kes, [[alternative HTML version deleted]] __ R-help@r-project.org 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] Basic questions about lme()
Hi, I have some basic questions about lme(), I have run following: Mod1-lme summary (Mod1) anova (Mod1) 1. What is the differece between the summary result and the anova result? 2. Is it sufficient to only report the anova result in an article? 3. How is the most proper way to describe the use of this statistics in the method chapter in a scientific article? 4. Is my suggestion below ok? And here is how I have described it in the method section: The lme function of the nlme package for R was used to fit linear mixed-effects (LME) models, using restricted maximum likelihood (REML). Model selection were computed by using the Akaike Information Criteria (AIC). The overall test of the model was conducted with ANOVA. Regards Kes, [[alternative HTML version deleted]] __ R-help@r-project.org 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] Is it possible with two random effects in lme()?
Dear all, Is it possible with two random effects in lme()? lmefit1- lme(Handling ~ Mass + factor(Prey)+ Mass*factor(Prey), random = ~ 1 |Place+Age) Here I use Place as random effect, but I also want to add Age as a random effect. Since there could be an effect of Age (continous variable), but I like to control for it rather than locking at the effect of Age on handling time, since Mass and Prey type are of main interest. Regards Kes, [[alternative HTML version deleted]] __ R-help@r-project.org 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] How to run interaction between to categoric variables in lme()?
Hello, How do I run interaction between to categoric variables in lme()? I tried this: lmefit1- lme(Handling ~Mass+factor(Prey)+factor (Decap)+ factor(Prey)*factor(Decap), random = ~ 1 |Place, data=nestling1) Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Regards Kes, [[alternative HTML version deleted]] __ R-help@r-project.org 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.
