[R-sig-ME] getting between groups variance when using (1|x:y)in the formula

[Hans Ekbrand]

On 2012-06-01 13:53, Ben Bolker wrote:
> Hans Ekbrand<hans at ...>  writes:
>
>    
>> On 2012-05-31 17:35, Hans Ekbrand wrote:
>>      
>>> Let's say I have a formula like this
>>>
>>> my.fit<- glmer(w ~ 1 + y + (1|x) + (1|x:y) + z)
>>>
>>> Then the summary() output gives information about variance and std.dev
>>> for the random term x:y
>>>
>>> and ranef(my.fit, postVar = TRUE) gives estimates and standard
>>> deviations for x and each value of x:y.
>>>
>>> Is there a way to get a single measure of the variance of y within x?
>>>        
>> I meant to say "a singe measure of the variance of y within x, for each
>> level of y".
>>
>>      
>     I don't think that's something that glmer() estimates -- it
> assumes that the variance is equal for every y-within-x combination.
> I suppose you could just compute the variance of each group of
> conditional modes, i.e. if xyests are your x:y conditional modes
> and xests are your x conditional modes then you could
> tapply(xyests,list(xests),var) ...  someone may suggest something
> better ...
>    

Thanks for your suggestion, Ben. I ended up doing like this.:

my.df <- ranef(my.fit, postVar = TRUE, whichel = "x:y")$x
my.var <- as.numeric(attr(my.df, "postVar"))
foo <- strsplit(rownames(my.df), ":")
the.names <- unique(sapply(1:nrow(my.df), function(x) {foo[[x]][2] }))
the.sd <- sapply(the.names, function(x) {
   these <- grep(paste(":", x, "$", sep = ""), rownames(my.df))
   sqrt(sum(my.var[these])/length(these))
})

I am not really sure about the meaningfulness of this measure, but it 
varied over the levels of y in the way I expected.