Message-ID: <6e8d8456-504a-17f0-14f8-728f38cad75e@phillipalday.com>
Date: 2021-06-07T15:30:44Z
From: Phillip Alday
Subject: Relationship between mixed-effects models and fixed-effects models
In-Reply-To: <27fda3d1-03dd-aa87-a1b8-01c03809ae7d@phillipalday.com>
Somewhat related to this and what James wrote, in the world of fMRI and
other two-stage analyses in psychology and neuroscience, the "fixed
effect" vs "random effect" distinction is used in the same sense as in
meta-analysis, which lines up more closely with the use in mixed models,
i.e. whether or not the individual estimates are treated as observed
draws from a random variable in the group-level analysis.
On 07/06/2021 10:27, Phillip Alday wrote:
> If I understand correctly, "fixed effects" in econometrics are simply
> categorical variables, especially ones with a large number of levels.
> There are "fixed" in the sense that they are observed at fixed
> (discrete) levels instead of as continuously.
>
> I don't have access to my copy at the moment, but this is discussed in
> Gelman & Hill (2006).
>
> Phillip
>
> On 07/06/2021 10:09, Douglas Bates wrote:
>> Occasionally I encounter discussions of what are called fixed-effects
>> models in econometrics but I haven't seen descriptions of the underlying
>> statistical model. Can anyone point me to a description of these models,
>> in particular a description in terms of a probability distribution of the
>> response? I would be particularly interested in a discussion of how they
>> relate to mixed-effects models as we think of them in lme4 and nlme.
>>
>> [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models