icc() returns the intraclass correlation – the proportion of variance
that lies between groups – for a mixed model with a single random-effect
term. For a biologist this is the repeatability of the trait.
The returned value carries a scale attribute that is essential to its
interpretation:
data scale (
scale = "data"): a Gaussian-identity fit with one random intercept. \(\sigma^2_g / (\sigma^2_g + \sigma^2_\varepsilon)\) is a genuine proportion of variance in the observed response.latent scale (
scale = "latent"): a binomial fit, where the residual is the known link-scale constant (\(\pi^2/3\) for logit, 1 for probit). This is repeatability on the latent (link) scale and is not a proportion of variance in the observed 0/1 outcome – the returned object carries that caption.
When the quantity is not defined – another family, a location-scale
Gaussian whose residual SD varies, or more than one random-effect term –
icc() returns NA with a human-readable reason attribute rather than a
misleading number. Use variance_partition() to see the full breakdown in
those cases. Point estimate only; no confidence interval.
Arguments
- x
A
symbolized_modelwhose underlying fit is retained onx$metadata$fit.- ...
Reserved for future use.
Value
A length-1 numeric (S3 class symbolizer_icc) with attributes
scale ("data", "latent", or NA), reason (character or NA), and
caption (character or NA). Prints a one-line reading at the console.
See also
variance_partition() for the full source-by-source breakdown.