Ok. Thank you both for clarifying this for me. 
-Dave



On Oct 17, 2013, at 11:05 PM, Ben Bolker wrote:

> On 13-10-17 08:28 PM, Dave Marvin wrote:
>> Sorry, I included it as a text file attachment. Guessing the
>> list-serv strips attachments... Here is a link to the text file:
>> http://goo.gl/e5q2hO
>> 
>> If that is the issue (which after looking back at my boxplot is
>> probably the case) should I still expect literally zero variance
>> attributed to the chambers?
> 
>  Yes.  This is a case, I think (referred to from time to time in
> threads on this list), where the classical method of moments estimates
> would give a negative among-group variance, or a compound symmetry model
> would give negative within-group correlations; the framework used in
> lme4 can't do either of those things easily.  (It would be entertaining
> but totally impractical to try to figure out what kind of imaginary- or
> complex-valued values one would need in the computations to get this to
> work out).
> 
>  Ben Bolker
> 
>> 
>> 
>> On Oct 17, 2013, at 8:16 PM, Ben Bolker wrote:
>> 
>>> Dave Marvin <marvs@...> writes:
>>> 
>>>> 
>>>> For the following dataset (described at the bottom of this
>>>> email),
>>> 
>>> Did you mean to include an actual data set, or just the text
>>> description? Without the data set itself, we can't do better than
>>> guessing.
>>> 
>>>> a boxplot of the data by chamber
>>>> 
>>>>> height=read.table("height.txt",header=TRUE) 
>>>>> boxplot(HtChg~Chamber,data=height)
>>> 
>>>> shows there is clearly a lot of chamber-to-chamber variation in
>>>> the response variable. However, if I run a random intercept-only
>>>> model:
>>> 
>>>>> lmer(HtChg~1+(1|Chamber),data=height)
>>>> 
>>>> I get 0 variance for the random intercept. Same is true if I then
>>>> include any categorical fixed effects. Does this seem correct,
>>>> and if so why? -Dave
>>> 
>>>>> I am analyzing the growth response (Height Change) of two
>>>>> plant
>>>> types (vines vs. trees) to different CO2 levels, for a mix of 
>>>> species of each plant type in plant growth chambers (Chamber).
>>>> CO2 and FT are categorical predictors, each with two levels 
>>>> (elevated/ambient CO2, vine/tree plant Functional Types). Each 
>>>> growth chamber had the same mix of 8 species (Spp).
>>> 
>>> Presumably the within-chamber variation is large enough that it
>>> adequately accounts for the among-chamber variation? Again, hard to
>>> say without seeing the data ... you could do the math yourself
>>> (e.g. is variance among >= (variance within)/(n within)?), or
>>> simulate some representative examples ...
>>> 
>>> _______________________________________________ 
>>> R-sig-mixed-models@r-project.org mailing list 
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>> 
> 


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