[R-sig-ME] Negative Variance

[Ben Bolker]

On 13-06-04 12:00 PM, Jarrod Hadfield wrote:
> Hi,
> 
> Negative variance estimates could make sense if viewed as covariances.
> For example, you could imagine controlling the amount of food for a nest
> of chicks very carefully such that negative correlations between the
> weights of nest-mates exist because of competition (if I take a large
> slice of the pie you're left with a little slice). Having a negative
> estimate of the nest variance would then make sense if viewed as an
> estimate of the covariance. asreml-R will allow you to let the variance
> go negative (or model them as residual correlations if you prefer).
> 
> Cheers,
> 
> Jarrod


  OK.  lme won't let variances go negative, but it will allow you to
estimate negative residual correlations:

lme(prevalence~sex,random=list(tripsite=pdCompSymm(~sex-1)),data=g6)

 is one example I quickly pulled out of a previous analysis (correlation
between male and female prevalences measured within a trip:site
combination, which could be either positive or negative).

  So far this is not easily done in lme4::lmer.




> 
> 
> Quoting Ben Bolker <bbolker at gmail.com> on Tue, 4 Jun 2013 15:44:51 +0000
> (UTC):
> 
>> Callie Baird <calliebaird at ...> writes:
>>
>>>
>>> I am trying to fit multilevel models, allowing negative variance
>>> estimates.
>>>  Is there a way to allow negative variance estimates as in nobound in
>>> SAS?
>>>
>>> Thanks,
>>>
>>> Rachel Baird
>>>
>>
>>   I don't know of one.  This is typically a 'feature' of
>> method-of-moments estimators; most of the approaches I know of
>> that are implemented in R use Bayesian or (restricted) maximum
>> likelihood approaches for which negative variances would be
>> completely nonsensical ...
>>
>>   Just out of curiosity, why would you _want_ negative variance
>> estimates ... ?  The only reason I can think of would be to
>> match previous estimates ...
>>
>>   Ben Bolker
>>
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>>
>>
> 
>