[R-sig-ME] Relationship between mixed-effects models and fixed-effects models
me @end|ng |rom ph||||p@|d@y@com
Mon Jun 7 17:30:44 CEST 2021
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).
> 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.
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