rmcorrShiny

rmcorrShiny computes and visualizes repeated measures correlation (rmcorr) to estimate the common linear within-individual association for paired repeated measures across multiple individuals.

Key Features:

• Repeated Measures Correlation Analysis: Calculates rmcorr to quantify within-individual linear associations while accounting for non-independence of repeated observations.
• Data Visualization: Generates graphical representations of within-individual associations across repeated measures.

Scientific Applications:

• Longitudinal and Repeated Measures Studies: Analyzes within-subject associations in fields such as psychology, medicine, and ecology where repeated measurements violate independence assumptions.

Methodology:

rmcorrShiny implements repeated measures correlation using a model analogous to a null multilevel framework with a fixed slope and varying intercepts per individual, preserving within-subject dependency structure in paired repeated data.