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Bolker (2015) talks of a research scenario in which site is the grouping factor. He writes on p.312 that

Treating site as a random effect compromises between the extremes of pooling and estimating separate (fixed) estimates; we acknowledge, and try to quantify, the variability in slope among sites. Because the trends are assumed to come from a population (of slopes) with a well-defined mean, the predicted slopes in CO2 flux for each site are a weighted average between the trend for that site and the overall mean trend across all sites; the smaller and noisier the sample for a particular site, the more its slope is compressed toward the population mean (figure 13.1). For technical reasons, these values (the deviation of each site’s value from the population average) are called conditional modes, rather than estimates. The conditional modes are also sometimes called random effects, but this could also refer to the grouping variables (the sites themselves, in the tundra example).

What are those technical reasons?

Bolker, B. M. (2015). Linear and generalized linear mixed models. In G. A. Fox, S. Negrete-Yankelevich, & V. J. Sosa (Eds.), Ecological statistics: Contemporary theory and application. Oxford University Press.

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    $\begingroup$ There is a nice discussion in this thread about the technical reasons. stats.stackexchange.com/questions/438427/… For a hint of what's going on, remember that although he doesn't call them such in the article cited, these are also referred to as Empirical Bayes predictions. $\endgroup$
    – Erik Ruzek
    May 4 '20 at 19:55

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