Re: [R] lme X lmer results

From: Dave Atkins <>
Date: Sun 01 Jan 2006 - 01:40:45 EST

Message: 18
Date: Fri, 30 Dec 2005 12:51:59 -0600
From: Douglas Bates <>
Subject: Re: [R] lme X lmer results
To: John Maindonald <> Cc:

        <> Content-Type: text/plain; charset=ISO-8859-1

On 12/29/05, John Maindonald <> wrote:

>> Surely there is a correct denominator degrees of freedom if the design
>> is balanced, as Ronaldo's design seems to be. Assuming that he has
>> specified the design correctly to lme() and that lme() is getting the df
>> right, the difference is between 2 df and 878 df. If the t-statistic
>> for the
>> second level of Xvar had been 3.0 rather than 1.1, the difference
>> would be between a t-statistic equal to 0.095 and 1e-6. In a design
>> where there are 10 observations on each experimental unit, and all
>> comparisons are at the level of experimental units or above, df for
>> all comparisons will be inflated by a factor of at least 9.

Doug Bates commented:

I don't want to be obtuse and argumentative but I still am not convinced that there is a correct denominator degrees of freedom for _this_ F statistic. I may be wrong about this but I think you are referring to an F statistic based on a denominator from a different error stratum, which is not what is being quoted. (Those are not given because they don't generalize to unbalanced designs.)

This is why I would like to see someone undertake a simulation study to compare various approaches to inference for the fixed effects terms in a mixed model, using realistic (i.e. unbalanced) examples.


Here is a paper that focused on the various alternatives to denominator degrees of freedom in SAS and does report some simulation results:

Not sure whether it argues convincingly one way or the other in the present discussion.

cheers, Dave

Dave Atkins, PhD

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Received on Sun Jan 01 03:04:37 2006

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