rptR

rptR estimates repeatability (R) and its uncertainty to quantify measurement reliability for traits with Gaussian, binomial, and Poisson distributions.

Key Features:

• Repeatability estimation: Estimates repeatability (R) and its associated uncertainty for measured traits.
• Supported distributions: Handles Gaussian, binomial, and Poisson-distributed traits.
• Raw variance computation: Computes raw variances as part of variance component estimation.
• Marginal R²: Computes marginal R² to quantify variance explained by fixed effects.
• Non-Gaussian theory: Implements theoretical methods for quantifying repeatability in non-Gaussian traits.
• Observer and method agreement metrics: Calculates inter-observer and intra-observer repeatabilities and agreement metrics between assessment methods.

Scientific Applications:

• Measurement reliability: Quantifying measurement repeatability and uncertainty in biological and ecological studies.
• Observer repeatability studies: Evaluating inter-observer and intra-observer repeatability for observational or scoring methods.
• Method comparison: Assessing agreement between diagnostic or assessment methods, such as palpation versus radiographic evaluation.
• Keel bone assessment example: Applied to evaluate repeatability of keel bone damage assessments in laying hens, including effects of training on repeatability for fractures and deviations (PMID: 31581757).

Methodology:

Estimation of repeatability (R) and its uncertainty for Gaussian, binomial, and Poisson traits, computation of raw variances and marginal R², and calculation of inter-observer and intra-observer repeatabilities and agreement metrics.