independent random effects with equal variances
On Wed, May 4, 2011 at 1:02 PM, Christos Hatzis
<christos.hatzis at nuverabio.com> wrote:
Independence, equal variance and the implicit normality assumption wouldn't imply that these random effects are IID from the same N(0, sigma) distribution? ?Wouldn't then this be equivalent to
y ~ x + (1|R)
where R is the "combined" random effect?
Except that you can't define a factor R with the combined levels. Consider, for example, the Penicillin data in the lme4 package. A model with independent random effects having one variance for the plate and one variance for the sample random effects has the model formula diameter ~ 1 + (1|plate) + (1|sample) for a total of 30 random effects (24 plates and 6 samples). You can't generate a factor with 30 levels that can be decomposed into 24 levels for plate and 6 levels for samples.
-----Original Message----- From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of Douglas Bates Sent: Wednesday, May 04, 2011 1:56 PM To: Hae Kyung Im Cc: r-sig-mixed-models at r-project.org Subject: Re: [R-sig-ME] independent random effects with equal variances On Wed, May 4, 2011 at 10:47 AM, Hae Kyung Im <haky at uchicago.edu> wrote:
Dear list,
does anyone know of an easy way to enforce equal variance for two
independent random effects?
So I would like to fit this model with equal variances for R1 and R2
y ~ x + (1|R1) + (1|R2)
I don't think that would be easily done under the current setup.
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