Relationship between mixed-effects models and fixed-effects models
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