Extract an experimental repeatability confidence interval — repeatability

Usage

repeatability_interval(object, ...)

Arguments

object: A fitted model object.
...: Unused. Extra arguments, including level, are an error because they would be ignored; the interval level is fixed at the engine value.

Value

A one-row data frame with estimate (the repeatability t), lower, upper, level, and se, for hsquared_fit objects that contain it.

Details

repeatability_interval() returns an experimental large-sample (logit delta-method) confidence interval for the repeatability coefficient t = (Va + Vpe) / Vp of the opt-in repeatability (permanent-environment) model, available only when the fit contains it. The interval is built from the observed information: a central finite-difference Hessian of the REML log-likelihood with fd_step = 1e-4, not the univariate average-information matrix. See the information-matrix table on Can I fit and report this?.

It mirrors the engine row V3-REPEAT-REML (partial): the engine's repeatability REML estimator and this interval are engine-internal self-consistency tested (recovery of t and interval bracketing / range / level-nesting / point-estimate match on seeded fixtures), but there is no external comparator, no h^2 interval, and no deep-pedigree validation. It is asymptotic, REML-only, unreliable at small n or near the (0, 1) boundary (where the engine throws and the field is omitted), and not a validated capability.