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A process feature should not be treated as an individual-difference measure until its dependability across items, sessions, and devices is quantified.
gstudy <- fit_process_gstudy(
process_long,
metric = "pupil_auc",
facets = c("person", "item", "session", "device")
)
process_variance_components(gstudy)
plot_variance_components(gstudy)
dstudy <- design_process_dstudy(
gstudy,
items = seq(5, 40, 5),
sessions = 1:4,
devices = 1:2
)
plot_dependability_surface(dstudy)
reliability <- audit_process_reliability(
process_long,
metrics = c("dwell_ms", "pupil_auc", "aoi_entropy"),
method = "icc"
)
plot_reliability_by_metric(reliability)Vendor-neutral import does not imply metric equivalence. Paired cross-device data can be linked and audited against a declared equivalence margin.
link <- fit_device_linking(
paired_device_data,
metric = "pupil_auc",
reference_device = "laboratory_reference",
id_cols = c("person_id", "trial_id")
)
plot_device_agreement(link)
plot_device_bias_by_magnitude(link)
plot_device_transfer_curve(link)
equivalence <- audit_device_equivalence(link, equivalence_margin = 0.05)
plot_device_equivalence_intervals(equivalence)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.