Re: [R] lsmeans

From: hadley wickham <>
Date: Sun, 08 Jun 2008 13:52:28 -0500

On Sun, Jun 8, 2008 at 12:58 PM, Douglas Bates <> wrote:
> On 6/7/08, John Fox <> wrote:
>> Dear Dieter,
>> I don't know whether I qualify as a "master," but here's my brief take on
>> the subject: First, I dislike the term "least-squares means," which seems to
>> me like nonsense. Second, what I prefer to call "effect displays" are just
>> judiciously chosen regions of the response surface of a model, meant to
>> clarify effects in complex models. For example, a two-way interaction is
>> displayed by absorbing the constant and main-effect terms in the interaction
>> (more generally, absorbing terms marginal to a particular term) and setting
>> other terms to typical values. A table or graph of the resulting fitted
>> values is, I would argue, easier to grasp than the coefficients, the
>> interpretation of which can entail complicated mental arithmetic.
> I like that explanation, John.
> As I'm sure you are aware, the key phrase in what you wrote is
> "setting other terms to typical values". That is, these are
> conditional cell means, yet they are almost universally misunderstood
> - even by statisticians who should know better - to be marginal cell
> means. A more subtle aspect of that phrase is the interpretation of
> "typical". The user is not required to specify these typical values -
> they are calculated from the observed data.

How does Searle's "population marginal means" fit in to this? The paper describes a PMM as "expected value of an observed marginal mean as if there were one observation in every cell." - which was what I thought happened in the effects display. Is this a subtly on the definition of typical, or is that PMM's are only described for pure ANOVA's (i.e. no continuous variables in model)?



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Received on Sun 08 Jun 2008 - 18:59:01 GMT

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