Here is my blog post veterinary requirements education (Newton)

]]>Human psychophysics and monkey recording studies traditionally have too few subjects per study to attempt generalisation to the population. An inference to the population then cannot be justified on the basis of the data. But we may make that inference based on the *assumption* that what holds for the group studied holds for the population. The latter assumption (often implicit) may be justified for certain questions. It is the reason why psychophycisists and monkey electrophysiologists care about their peers’ results.

So I would argue that it is *incorrect* to say that type-1 error is inflated in fixed-effects analyses, because “type-1 error” in this statement refers to a hypothesis test that hasn’t been attempted (i.e. a population-level hypothesis test).

The question then becomes whether the interpretation in the papers goes beyond the animals studied, without the proper caveat that this inference is not supported by the statistics (but requires the prior belief that what goes for this group holds in general).

]]>“So even if we are willing to rely on hierarchical ordering and posit that within-subject variance is greater than between-subject variance (implying intraclass correlation is less than 0.5), it still might not be true that within-subject variance is greater than between-subject variance + subject-by-condition interaction variance.” ]]>

“So even if we are willing to rely on hierarchical ordering and posit that within-subject variance > between-subject variance (implying intraclass correlation between-subject variance + subject-by-condition interaction variance.” ]]>