I am confused about the expression "fixed effect" in the context of mixed models. I am more familiar with the terms like "fixed effects" and "random effects" in context of econometrics and the analysis of panel data.
The understanding of "random effects" seems similar in both disciplines and the "random effects model" in econometrics is equivalent to a "mixed model with random intercept". See for example: How exactly does a "random effects model" in econometrics relate to mixed models outside of econometrics?
But what is about the "fixed effect". In econometrics, with the help of fixed effects e.g. all time invariant effects will be absorbed. Or in other words, a dummy variable for each individual is introduced.
But, what is "fixed effect" in context of mixed models? In simple words? Hereby, I mean more the intuition and not the mathematically way.
It is not the same as a fixed effect in econometrics. That is what I understand, but I have no clue what it is instead.
Meanwhile I found this explanation in context of mixed models:
"The fixed effects are analogous to standard regression coefficients and are estimated directly."
This means to me, that a fixed effect in mixed models is not the same as fixed effects in econometrics. Or in other words: Fixed effects are the variables that are not declared as random effects (--> standard regression coefficients as in linear regression).
Source (slide 2): http://fmwww.bc.edu/EC-C/S2013/823/EC823.S2013.nn07.slides.pdf