compute_ICC: Compute Intraclass Correlation Coefficient (ICC) for Selected...

In scaledescr: Descriptive, Reliability, and Inferential Tables for Psychometric Scales and Demographic Data

Compute Intraclass Correlation Coefficient (ICC) for Selected Columns

Description

Computes Intraclass Correlation Coefficients (ICC) for a specified set of numeric variables within a data frame using psych::ICC().

This function standardizes column selection and basic validation while delegating all statistical estimation to psych::ICC().

Usage

compute_ICC(data, items, check_numeric = TRUE, lmer = FALSE, ...)

Arguments

data	A data frame containing the ratings or measurements.
items	A character vector specifying column names for which ICC should be calculated (e.g., raters or repeated measurements).
check_numeric	Logical. If TRUE (default), ensures all selected columns are numeric.
lmer	Logical. Passed to psych::ICC(). Default is FALSE.
...	Additional arguments passed to psych::ICC().

Details

The function does not choose or filter specific ICC models. All available ICC types (e.g., ICC1, ICC2, ICC3, single and average) are returned exactly as produced by psych::ICC().

Users are responsible for:

• Choosing the appropriate ICC model for their study design.

• Ensuring assumptions (e.g., continuous ratings, independence).

• Handling missing data appropriately.

Value

An object returned by psych::ICC(), typically a list containing a results table with ICC estimates, F statistics, confidence intervals, and model details.

See Also

ICC

scaledescr documentation built on April 11, 2026, 5:07 p.m.