Nothing
## ----include=FALSE------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE)
## -----------------------------------------------------------------------------
# validation <- run_model_validation(
# simulator = simulate_model,
# fitter = fit_model,
# extractor = extract_estimates,
# truth_extractor = extract_truth,
# grid = expand.grid(n_person = c(200, 500), n_item = c(20, 40)),
# spec = model_validation_spec(replications = 500)
# )
# model_validation_summary(validation)
# plot(validation, type = "coverage")
## -----------------------------------------------------------------------------
# grouped_cv(model_data, score ~ process_feature, group = "participant_id")
# crossed_grouped_cv(
# model_data,
# score ~ process_feature,
# groups = c("participant_id", "item_id")
# )
# quantify_process_leakage(model_data, score ~ process_feature)
## -----------------------------------------------------------------------------
# multiverse <- preprocessing_multiverse(
# dataset,
# specifications = preprocessing_grid,
# transform = preprocess_eye,
# analyse = fit_declared_model,
# extract = extract_target_estimand
# )
# plot(multiverse)
## -----------------------------------------------------------------------------
# create_public_benchmark(dataset, "benchmark", include_samples = FALSE, overwrite = TRUE)
# write_software_paper_scaffold("paper/eyeprocess-software-paper.Rmd")
## -----------------------------------------------------------------------------
# full_design <- advanced_validation_grid()
# validation_result <- run_model_validation(
# simulator = simulate_advanced_process_data,
# fitter = fit_candidate_model,
# extractor = extract_candidate_parameters,
# truth_extractor = function(x) x$truth,
# grid = full_design,
# spec = model_validation_spec(replications = 500L),
# seed = 20260804L
# )
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