[R-sig-ME] [EXT] ICC in lmer

[Daniel Lüdecke]

The `summary()` method does not include the ICC. You can, however, use
`performance::icc()` (see
https://easystats.github.io/performance/reference/icc.html) to compute the
ICC; or use packages that create summary outputs including ICC, like the
modelsummary package. The parameters package, which returns "tidy" data
frames of regression results (similar to broom, but with more extra features
and nice printing) at least includes marginal/conditional R2.

library(lme4)
library(modelsummary)
library(parameters)

m <- lmer(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)
modelsummary(m)
model_parameters(m, summary = TRUE)

Daniel

-----Ursprüngliche Nachricht-----
Von: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> Im
Auftrag von J.D. Haltigan
Gesendet: Sonntag, 4. Juni 2023 06:11
An: r-sig-mixed-models <r-sig-mixed-models using r-project.org>
Betreff: [EXT] [R-sig-ME] ICC in lmer

Hi:

This may have already been covered though I did not see it in the archives
after a quick search. For linear mixed models, is there a way to get lmer
to calculate the ICC automatically so as to appear in the summary output?

Thanks,
JD

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