Relative Measurement Uncertainty (RMU)

Bayesian-style reliability estimate (Bignardi, Kievit & Bürkner, 2025) computed from a matrix of posterior or plausible-value draws. The columns of input_draws are split at random into two halves; reliability is the Pearson correlation across persons of paired columns from the two halves, summarised across pairs as a posterior mean with HDCI.

Usage

RMUreliability(input_draws, level = 0.95, verbose = FALSE)

Arguments

input_draws

Numeric matrix or data.frame of draws. Rows are subjects; columns are draws. Must have at least two columns; ideally many.

level

Numeric in (0, 1). Width of the HDCI returned. Default 0.95.

verbose

Logical. Print summary information about the input. Default FALSE.

Value

A 1-row data.frame with columns rmu_estimate, hdci_lowerbound, hdci_upperbound, plus the .width/.point/.interval metadata columns added by ggdist::mean_hdci().

Details

Adapted (with permission, GPL-2/3) from https://github.com/giac01/gbtoolbox/blob/main/R/reliability.R.

The function silently returns 0 for any column pair where either side has zero variance (the correlation is undefined there).

Requires the ggdist package (Suggests).

References

Bignardi, G., Kievit, R., & Bürkner, P. C. (2025). A general method for estimating reliability using Bayesian Measurement Uncertainty. PsyArXiv. doi:10.31234/osf.io/h54k8_v1

See also

RMreliability()