[R] Simple lme/lmer random effects questions

[Mark Difford]

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
> 
> ______________________________________________
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