iccMixed: Intraclass Correlation Coefficient (ICC) from Mixed Models

In JWiley/multilevelTools: Multilevel and Mixed Effects Model Diagnostics and Effect Sizes

Intraclass Correlation Coefficient (ICC) from Mixed Models

Description

This function estimates the ICC from mixed effects models estimated using lme4.

Usage

iccMixed(dv, id, data, family = c("gaussian", "binomial"))

Arguments

dv	A character string giving the variable name of the dependent variable.
id	A character vector of length one or more giving the ID variable(s). Can be more than one.
data	A data.table containing the variables used in the formula. This is a required argument. If a data.frame, it will silently coerce to a data.table. If not a data.table or data.frame, it will attempt to coerce, with a message.
family	A character vector giving the family to use for the model. Currently only supports “gaussian” or “binomial”.

Value

A data table of the ICCs

References

For details, see Campbell, M. K., Mollison, J., and Grimshaw, J. M. (2001) <doi:10.1002/1097-0258(20010215)20:3 "Cluster trials in implementation research: estimation of intracluster correlation coefficients and sample size."

Examples

iccMixed("mpg", "cyl", mtcars)
iccMixed("mpg", "cyl", data.table::as.data.table(mtcars))
iccMixed("mpg", "cyl", data.table::as.data.table(mtcars), family = "gaussian")
iccMixed("mpg", c("cyl", "am"), data.table::as.data.table(mtcars))
iccMixed("am", "cyl", data.table::as.data.table(mtcars), family = "binomial")

JWiley/multilevelTools documentation built on April 1, 2024, 9:56 p.m.