Useful before many-facet IRT: quantifies how much variance comes from person,
item, device, session, algorithm, and residual sources.
Usage
generalizability_process_study(data, outcome, facets, REML = TRUE)
Arguments
- data
Input data frame or compatible tabular object.
- outcome
Outcome variable.
- facets
Facet variables included in the analysis.
- REML
Whether restricted maximum likelihood is used.
Value
An object of class "eye_process_g_study", stored as a named list, with components "model", "variance_components", "facets", "outcome". It contains generalizability-style variance decomposition for a process measure and associated metadata or diagnostics needed to interpret the result.
