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I would like to perform post-hoc analysis on adjusted variances rather than on adjusted means (lsmeans or emmeans). Is it possible to calculate adjusted variances? and to compare them?

I have two different linear models:

model1 = lm((Phenotype)~ Batch + Tray + Genotype, data=data)
model2 = glm((Phenotype)~ Batch + Tray + Genotype, data=data, family = binomial())

I expect to obtain adjusted variances from linear models.

Thanks for your help,

LM

user21260341
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    Your question is unclear (and off-topic here). You need to specify the estimates for which you want to analyze variances. I'm also not familar with the concept of "adjusted variances" in the context of multiple comparisons. Usually, p-values are adjusted. – Roland Feb 22 '23 at 07:09

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