Hi Brandon, >> ...is it sufficient to leave the values as they are or should I generate >> unique names for all >> combinations of sleeve number and temperature, using something like >> > data$sleeve.in.temp <- factor(with(data, temp:sleeve)[drop=TRUE])
You might be luckier posting this on https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models You need to make a unique identifier for each of your five sets of sleeves (or you need to nest sleeve in temp) if you wish to take account of that structure (temp/sleeve) as a random effect. I could be mistaken, but I think there are subtle differences between ~ 1|temp/sleeve and ~ 1|data$sleeve.in.temp designs. >> confused on how to actually set up the random effects term for the >> models. Given my experimental setup, using the lme syntax... The difference between (1) random = ~ 1|sleeve, ... and (2) random = ~ 1+temp|sleeve is that the first will give a random intercept for each level of sleeve, but the slope is fixed to be the same as their is no random term for slope. In the second specification there is a random term for slope, viz temp, so both intercepts and slopes can --- and probably will --- vary. ## To get some idea of what's being done, look at the following example. ## random intercepts, parallel slopes mod1 <- lme(distance ~ age, Orthodont, random = ~ 1 | Subject) ## random intercepts, separate slopes mod2 <- lme(distance ~ age, Orthodont, random = ~ age | Subject) plot(augPred(mod1, primary=~age)) ## parallel slopes plot(augPred(mod2, primary=~age)) ## separate slopes HTH, Mark. Brandon Invergo wrote: > > Hello, > > I have two very rudimentary questions regarding the random effects terms > in the lme and lmer functions. I apologize if this also partly strays > into a general statistics question, but I'm a bit new to this all. So > hopefully it'll be a quick problem to sort out... > > Here is my experimental setup: I raised butterflies in 5 different > testing chambers all set to different temperatures. Within the testing > chambers, the butterflies were held in 10 different sleeves, which were > rotated daily to compensate for microenvironmental effects. I measured > several traits of the butterflies and I am constructing models for each > trait (unfortunately, multivariate analysis isn't possible). In my > models, sex and temperature are fixed factors and the sleeve is a random > effect. Most of the response variables are normally distributed, but > there is one with a Gamma distribution (time until an event) and another > with poisson distribution (counts), so some models use lme while others > use lmer. I would like to determine if, despite the daily rotation, > there are still random effects from the individual sleeves. My two > questions (assuming I haven't already made grave errors in my > description of the setup) are: > > 1) In my data file, the "sleeve" variable is just marked with a number 1 > through 10; the temperature is noted in a different column, so the 50 > sleeves do not have unique names, but rather there are 5 instances of > each of the 10 sleeve numbers. If sleeve is to be properly included in > the models as a random effect, is it sufficient to leave the values as > they are or should I generate unique names for all combinations of > sleeve number and temperature, using something like > > data$sleeve.in.temp <- factor(with(data, temp:sleeve)[drop=TRUE]) > > > 2) (this is the one that strays more into standard statistics territory, > sorry) I'm a bit confused on how to actually set up the random effects > term for the models. Given my experimental setup, using the lme syntax, > should it be: > > model <- lme(response ~ sex*temp, random=~temp|sleeve, data) > or > > model <- lme(response ~ sex*temp, random=~1|sleeve, data) > or something else? I've searched and searched, but everything I find > online seems to be significantly more advanced than what I'm doing, > leaving me even more confused than when I started! > > > Thank you very much for your help!! I want to be sure I do this analysis > right.... > Cheers, > -brandon > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/Simple-lme-lmer-random-effects-questions-tp18933698p18939376.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
