Package index • eyeprocess

Validation evidence programmes and freezing (0.9 M2)

evaluate_validation_acceptance(): Evaluate a validation acceptance rule
expand_eyeprocess_stress_evidence_plan(): Expand a stress evidence plan into one-factor-at-a-time scenarios
expand_eyeprocess_validation_plan(): Expand a validation-evidence plan to a scenario table
eyeprocess_irt_engine_evidence_table(): Build an external-engine capability and availability table
eyeprocess_irt_precision_evidence_table(): Build a paper-ready IRT information/precision table
eyeprocess_negative_control_evidence_plan(): Declare negative-control evidence targets
eyeprocess_negative_control_evidence_table(): Build a paper-ready negative-control table
eyeprocess_recovery_evidence_table(): Build a paper-ready parameter-recovery table
eyeprocess_reliability_evidence_plan(): Declare reliability evidence targets
eyeprocess_reliability_evidence_table(): Build a paper-ready reliability table
eyeprocess_sbc_evidence_table(): Build a paper-ready SBC table
eyeprocess_stress_evidence_plan(): Declare the Milestone #2 measurement-quality stress evidence plan
summarise_eyeprocess_stress_evidence(): Summarise executed measurement-stress evidence
run_eyeprocess_stress_evidence(): Execute a declared measurement-stress evidence plan
eyeprocess_stress_evidence_table(): Build a paper-ready stress-test table
eyeprocess_validation_atlas_gaps(): Summarise gaps in a validation evidence atlas
eyeprocess_validation_claim_matrix(): Build a machine-readable validation claim/evidence matrix
eyeprocess_validation_evidence_atlas(): Assemble a validation evidence atlas
eyeprocess_validation_evidence_grade(): Grade the completeness of validation evidence
eyeprocess_validation_evidence_index(): Create an index over frozen validation evidence artifacts
eyeprocess_validation_evidence_manifest(): Create an evidence manifest from files and in-memory objects
eyeprocess_validation_plan(): Declare an eyeprocess validation-evidence plan
eyeprocess_validation_readiness(): Evaluate readiness of a Milestone #2 validation evidence bundle
eyeprocess_validation_release_gate(): Apply a conservative software-release evidence gate
eyeprocess_validation_seed(): Derive a deterministic bounded validation seed
freeze_eyeprocess_validation_atlas(): Freeze a validation atlas with a reproducibility fingerprint
freeze_eyeprocess_validation_evidence(): Freeze a complete Milestone #2 evidence bundle
read_eyeprocess_validation_evidence(): Read and verify a frozen evidence bundle
read_validation_scenario_manifest(): Read a validation scenario manifest
summarise_validation_acceptance(): Summarise an acceptance matrix
validate_eyeprocess_validation_plan(): Validate a validation-evidence plan
validation_acceptance_matrix(): Evaluate a table against named validation rules
validation_acceptance_rule(): Define a validation acceptance rule
validation_mcse_profile(): Estimate Monte Carlo uncertainty for validation summaries
validation_replication_budget(): Compute a replication budget from a target MCSE
validation_scenario_manifest(): Create a scenario manifest for frozen validation work
verify_eyeprocess_validation_atlas(): Verify a frozen validation atlas
verify_eyeprocess_validation_evidence(): Verify the integrity hash of a frozen evidence bundle
write_eyeprocess_validation_evidence(): Write a frozen evidence bundle
write_eyeprocess_validation_report(): Write a compact Markdown validation report
write_validation_scenario_manifest(): Write a validation scenario manifest

IRT foundations, information, scoring, and diagnostics (0.9 M2)

eyeprocess_irt_2pl_probability(): 2PL item-response probability
eyeprocess_irt_3pl_probability(): 3PL item-response probability
eyeprocess_irt_4pl_probability(): 4PL item-response probability
eyeprocess_irt_adaptive_trace(): Create an auditable adaptive-testing trace
eyeprocess_irt_bank_coverage(): Audit item-bank information coverage across a theta region
eyeprocess_irt_category_function_audit(): Audit category probability functions
eyeprocess_irt_classification_precision(): Summarise decision precision at one or more theta cut scores
eyeprocess_irt_conditional_sem(): Conditional standard error from information
eyeprocess_irt_content_balance_audit(): Audit content balance in an administered adaptive form
eyeprocess_irt_eap_score(): EAP score for dichotomous IRT item parameters
eyeprocess_irt_expected_score(): Expected item score
eyeprocess_irt_exposure_summary(): Summarise item exposure rates
eyeprocess_irt_extreme_score_audit(): Audit extreme response scores without assigning behavioral labels
eyeprocess_irt_fit_dashboard(): Build an integrated IRT diagnostic dashboard object
eyeprocess_irt_gpcm_probability(): Generalized partial-credit category probabilities
eyeprocess_irt_grm_probability(): Graded-response category probabilities
eyeprocess_irt_identification_audit(): Audit IRT scale/location identification
eyeprocess_irt_infit_outfit(): Compute residual-based Infit and Outfit summaries
eyeprocess_irt_information_area(): Area under an information curve
eyeprocess_irt_information_gain(): Information gain between two conditional standard errors
eyeprocess_irt_information_targeting(): Audit how well item information targets a theta distribution
eyeprocess_irt_item_bank(): Item bank object for adaptive design
eyeprocess_irt_item_fit_residuals(): Compute item residual fit summaries from observed and predicted probabilities
eyeprocess_irt_item_information(): Compute item information for transparent IRT families
eyeprocess_irt_item_selection(): Select the most informative eligible item at a theta estimate
eyeprocess_irt_local_dependence_pairs(): Extract high residual-dependence item pairs
eyeprocess_irt_map_score(): MAP score for dichotomous IRT item parameters
eyeprocess_irt_marginal_reliability(): Marginal reliability from latent-score variance and conditional error variance
eyeprocess_irt_measurement_precision_profile(): Summarise measurement precision across a theta region
eyeprocess_irt_missing_by_design_audit(): Audit missing-by-design structure in an IRT response matrix
eyeprocess_irt_mle_score(): Bounded ML score for dichotomous IRT item parameters
eyeprocess_irt_model_card(): Create a governed IRT model card
eyeprocess_irt_model_card_audit(): Audit completeness of an IRT model card
eyeprocess_irt_model_spec(): Declare an eyeprocess IRT model specification
eyeprocess_irt_monotonicity_audit(): Audit monotonicity of an item response curve
eyeprocess_irt_nominal_probability(): Nominal-response category probabilities
eyeprocess_irt_parameter_plausibility_audit(): Audit basic plausibility of dichotomous item parameters
eyeprocess_irt_person_fit_lz(): Standardized log-likelihood person-fit diagnostic
eyeprocess_irt_person_fit_residuals(): Compute person residual fit summaries
eyeprocess_irt_plausible_values(): Draw plausible values from a discrete posterior grid
eyeprocess_irt_ppc_discrepancy(): Compare observed and replicated IRT discrepancy statistics
eyeprocess_irt_prior_sensitivity_grid(): Construct a prior-sensitivity grid for Bayesian IRT analyses
eyeprocess_irt_prior_sensitivity_summary(): Summarise sensitivity of an estimand across declared prior specifications
eyeprocess_irt_prior_spec(): Declare prior families for Bayesian IRT engine adapters
eyeprocess_irt_process_aware_selection_penalty(): Process-aware selection penalty without mental-state inference
eyeprocess_irt_q3(): Compute Yen-style Q3 residual correlations
eyeprocess_irt_score_table(): Score a response matrix with EAP, MAP, or ML
eyeprocess_irt_score_uncertainty(): Summarise score uncertainty
eyeprocess_irt_sparse_design_audit(): Audit sparse person-item response coverage
eyeprocess_irt_stopping_rule(): Evaluate a simple adaptive stopping rule
eyeprocess_irt_targeting_gap(): Compare an examinee distribution with item-bank targeting
eyeprocess_irt_test_characteristic_curve(): Test characteristic curve for dichotomous item parameters
eyeprocess_irt_test_information(): Compute a test information curve from item parameters
eyeprocess_irt_threshold_order_audit(): Audit ordered category thresholds
validate_eyeprocess_irt_item_bank(): Validate an adaptive IRT item bank
validate_eyeprocess_irt_model_spec(): Validate an eyeprocess IRT model specification

IRT linking, invariance, process, and external engines (0.9 M2)

eyeprocess_irt_anchor_audit(): Audit candidate anchor items using supplied DIF evidence
eyeprocess_irt_anchor_purification(): Iteratively remove anchors exceeding a supplied effect threshold
eyeprocess_irt_apply_link(): Apply linear IRT scale-linking coefficients
eyeprocess_irt_device_drift(): Summarise parameter drift across acquisition devices
eyeprocess_irt_dif_effect_curve(): Differential item functioning effect curve from two parameter sets
eyeprocess_irt_dtf_curve(): Differential test functioning effect curve
eyeprocess_irt_engine_registry(): Registry of specialized external IRT engines
eyeprocess_irt_engine_status(): Query an external IRT engine
eyeprocess_irt_functioning_effect_summary(): Summarise DIF/DTF curve magnitude
eyeprocess_irt_haebara_link(): Haebara item-characteristic-curve linking
eyeprocess_irt_invariance_evidence(): Combine invariance evidence without converting it to a binary validity claim
eyeprocess_irt_link_stability(): Compare linking estimates across anchor subsets
eyeprocess_irt_mean_mean_link(): Mean-mean IRT linking coefficients
eyeprocess_irt_mean_sigma_link(): Mean-sigma IRT linking coefficients
eyeprocess_irt_process_alignment(): Align item parameters with process-channel summaries
eyeprocess_irt_process_dif_concordance(): Compare psychometric DIF effect sizes with process-channel contrasts
eyeprocess_irt_session_drift(): Summarise item-parameter drift over sessions
eyeprocess_irt_stocking_lord_link(): Stocking-Lord characteristic-curve linking
eyeprocess_joint_process_irt_spec(): Declare a response/process joint IRT specification
eyeprocess_multichannel_measurement_map(): Construct a multichannel measurement map
eyeprocess_process_irt_data_bundle(): Prepare a sparse response/process bundle for external joint engines
eyeprocess_process_item_profile(): Aggregate process channels by item
eyeprocess_process_missingness_pattern(): Summarise missingness patterns across response and process channels
eyeprocess_process_person_profile(): Aggregate process channels by person
eyeprocess_response_time_profile(): Summarise response-time structure for joint IRT work
eyeprocess_speed_accuracy_profile(): Describe speed-accuracy association without causal interpretation
fit_eyeprocess_erm(): Fit an eRm Rasch-family model without fallback substitution
fit_eyeprocess_gdina(): Fit a G-DINA cognitive-diagnosis model without fallback substitution
fit_eyeprocess_lnirt(): Fit a joint response/response-time LNIRT model without fallback substitution
fit_eyeprocess_mirt(): Fit a model with mirt without substituting another estimator
fit_eyeprocess_tam(): Fit a TAM model without substituting another estimator
run_eyeprocess_equateirt(): Run a named equateIRT linking/equating function without fallback substitution
run_eyeprocess_mirtcat(): Run a mirtCAT adaptive-testing workflow without fallback substitution
simulate_eyeprocess_catr(): Run a catR adaptive-testing simulation without fallback substitution
validate_eyeprocess_external_irt_fit(): Validate that an external IRT fit used the requested engine
validate_eyeprocess_joint_process_irt_spec(): Validate a joint process IRT specification

IRT recovery, multidimensional models, and cognitive diagnosis (0.9 M2)

eyeprocess_cdm_attribute_profiles(): Enumerate latent attribute profiles
eyeprocess_cdm_classification_uncertainty(): Summarise CDM classification uncertainty from profile probabilities
eyeprocess_cdm_dina_ideal_response(): Compute deterministic DINA ideal responses from a Q-matrix
eyeprocess_cdm_dina_probability(): DINA response probabilities from slip and guess parameters
eyeprocess_cdm_qmatrix_audit(): Audit a cognitive-diagnosis Q-matrix
eyeprocess_irt_latent_regression_design(): Build a latent-regression design matrix with explicit centering metadata
eyeprocess_irt_misspecification_metrics(): Compare recovery under reference and misspecified scenarios
eyeprocess_irt_misspecification_suite(): Create a model-misspecification suite
eyeprocess_irt_recovery_design(): Create an IRT recovery design
eyeprocess_irt_recovery_failures(): Summarise recovery failure rates
eyeprocess_irt_recovery_summary(): Summarise IRT parameter recovery
run_eyeprocess_irt_ability_sbc(): Run simulation-based calibration for known-item IRT ability scoring
eyeprocess_irt_sbc_ranks(): Construct SBC ranks from scalar truths and posterior draws
eyeprocess_irt_sbc_summary(): Summarise IRT SBC ranks with the package SBC diagnostics
eyeprocess_irt_testlet_audit(): Audit testlet sizes and singleton structures
eyeprocess_irt_testlet_spec(): Declare a testlet structure for bifactor/two-tier IRT engines
eyeprocess_mirt_directional_information(): Directional multidimensional 2PL information
eyeprocess_mirt_information_matrix(): Multidimensional 2PL item information matrix
eyeprocess_mirt_loading_audit(): Audit multidimensional IRT loading coverage
eyeprocess_mirt_loading_spec(): Declare a multidimensional IRT loading structure
freeze_eyeprocess_irt_reference(): Freeze IRT validation reference summaries
run_eyeprocess_irt_recovery(): Run IRT parameter recovery with the exact mirt engine
simulate_eyeprocess_irt_binary(): Simulate dichotomous IRT responses with optional local dependence and missingness

Validation, sensitivity, and negative controls (0.9)

audit_temporal_leakage(): Audit temporal leakage in a feature provenance table
calibration_sensitivity_grid(): Sensitivity grid for deterministic calibration offsets
compare_aoi_methods(): Compare explicit AOI assignment methods
compare_decision_manifests(): Compare two research decision manifests
compare_fixation_methods(): Compare explicit fixation-detection methods
compare_hard_probabilistic_aoi(): Compare hard and probabilistic AOI assignments
compare_process_models(): Compare explicit process-model specifications
compare_pupil_preprocessing(): Compare explicit pupil-preprocessing methods
compare_reproducibility_fingerprints(): Compare two reproducibility fingerprints
coverage_calibration_curve(): Interval coverage calibration curve
decision_space_coverage(): Coverage of a declared decision space by evaluated specifications
decision_stability(): Overall decision-stability summary
expand_process_validation_design(): Expand a process-validation design into explicit conditions
freeze_validation_reference(): Freeze a compact validation reference for regression testing
negative_control_concordance(): Concordance of multiple negative-control families
placebo_window_audit(): Audit a placebo/pre-event window
process_feature_time_provenance(): Declare temporal provenance for process features
process_measure_coverage(): Process-measure coverage for an observed dataset
process_negative_control_permute(): Permutation negative control
process_negative_control_shift(): Temporal-shift negative control
process_sensitivity_grid(): Construct an explicit process-analysis sensitivity grid
process_temporal_stability(): Pairwise temporal stability across sessions
process_validation_design(): Define an empirical process-validation design
pupil_baseline_sensitivity(): Evaluate pupil baseline-window sensitivity
run_process_negative_controls(): Run repeated process negative controls
run_process_sensitivity(): Run an explicit process-analysis multiverse
run_process_validation(): Run an empirical process-validation programme
sbc_ecdf_deviation(): ECDF deviation summary for SBC ranks
sbc_rank_diagnostics(): Build SBC rank diagnostics
sensitivity_branch_fingerprint(): Stable fingerprint of a sensitivity branch
sensitivity_decision_leverage(): Decision leverage of each analytical choice
sensitivity_fragility_index(): Fragility index across analysis specifications
sensitivity_multiverse_manifest(): Machine-readable multiverse manifest
sensitivity_rank_stability(): Rank stability across specifications
sensitivity_sign_stability(): Effect-sign stability across specifications
sensitivity_significance_stability(): Significance-decision stability across specifications
sensitivity_threshold_stability(): Substantive-threshold stability across specifications
simulate_process_validation_data(): Simulate a generic multimodal validation dataset with known truth
simulation_rank_statistic(): Compute a simulation-based calibration rank statistic
software_paper_coverage(): Compute descriptive evidence coverage
software_paper_validation_table(): Summarise validation evidence for a software paper
specification_coverage(): Fraction of planned specifications successfully evaluated
summarise_process_negative_controls(): Summarise process negative controls
summarise_process_sensitivity(): Summarise process sensitivity results
summarise_process_validation(): Summarise a process-validation result
validate_feature_availability(): Validate feature availability against an analysis cutoff
validate_process_validation_design(): Validate a process-validation design
validation_condition_id(): Return stable validation condition identifiers
validation_condition_ranking(): Rank validation conditions by a transparent robustness score
validation_coverage_table(): Interval-coverage table
validation_evidence_matrix(): Create a model-by-evidence validation matrix
validation_failure_profile(): Failure profile for a validation programme
validation_summary_mcse(): Monte Carlo standard-error diagnostics for validation summaries
validation_recovery_table(): Parameter-recovery table
validation_robustness_score(): Overall validation robustness score

Governed pipelines, decisions, and API lifecycle (0.9)

analysis_decision_entropy(): Entropy of an explicitly enumerated analysis-decision space
api_family_map(): Map exported APIs to conceptual families
api_lifecycle_diff(): Compare two API lifecycle registries
api_surface_summary(): Summarise API surface by family and lifecycle status
audit_eye_pipeline(): Audit a pipeline definition or completed run
canonical_eye_api(): Canonical API mapping
decision_manifest_diff(): Alias for manifest comparison emphasizing changed decision paths
decision_manifest_hash(): Stable hash of decision content
decision_manifest_table(): Flatten a decision manifest to a table
export_eye_pipeline(): Export a pipeline manifest and optional run status
eye_analysis_pipeline(): Construct a governed analysis pipeline
eye_analysis_spec(): Define explicit analysis decisions for an eyeprocess workflow
eye_api_inventory(): Inventory the public eyeprocess API
eye_api_lifecycle(): Normalize or create an API lifecycle registry
eye_api_recommendation(): Lifecycle recommendation for API review
eye_api_status(): Lookup lifecycle status for one or more APIs
eye_api_superseded(): Return superseded/deprecated compatibility interfaces
eye_decision_manifest(): Create a machine-readable research decision manifest
eye_pipeline_dot(): Render pipeline dependencies as Graphviz DOT
eye_pipeline_graph(): Return pipeline vertices and dependency edges
eye_pipeline_manifest(): Machine-readable pipeline manifest
eye_pipeline_mermaid(): Render pipeline dependencies as Mermaid flowchart text
eye_pipeline_step(): Define a governed pipeline step
eye_targets_manifest(): Create a targets-compatible dependency manifest
lock_decision_manifest(): Lock a decision manifest by content hash
outcome_blind_feature_audit(): Audit whether candidate predictors can be constructed without an outcome column
outcome_blind_snapshot(): Create an outcome-blind data snapshot
pipeline_failures(): Return failed pipeline steps
pipeline_result(): Extract a pipeline result by step name
pipeline_step_status(): Pipeline step status table
read_api_lifecycle_registry(): Read API lifecycle registry from CSV
read_decision_manifest(): Read a decision manifest written by eyeprocess
register_eye_api_status(): Add or update API lifecycle metadata without global mutation
resume_eye_pipeline(): Resume a governed pipeline from a prior run
run_eye_pipeline(): Run a governed eyeprocess pipeline
stress_test_process_pipeline(): Stress-test an analysis under explicit synthetic corruptions
validate_decision_manifest(): Validate a research decision manifest
validate_eye_pipeline(): Validate a governed eyeprocess pipeline
verify_decision_manifest_lock(): Verify that a locked manifest has not changed
verify_outcome_blind_snapshot(): Verify an outcome-blind snapshot has not changed
write_api_lifecycle_registry(): Write API lifecycle registry to CSV
write_decision_manifest(): Write a decision manifest
write_eye_pipeline_report(): Write a conservative pipeline report
write_eye_targets_template(): Write an explicit `_targets.R` template from a governed pipeline

Measurement reliability, quality, and stress testing (0.9)

analysis_resolution_guard(): Audit compatibility between measurement resolution and an analysis target
aoi_membership_probability(): AOI membership probabilities from uncertainty draws
apply_synthetic_corruption(): Apply a synthetic corruption plan
audit_pupil_preprocessing_order(): Audit declared order of pupil preprocessing steps
audit_sampling_irregularity(): Audit sampling irregularity
benchmark_memory_estimate(): Memory estimate for an R object or generated problem size
benchmark_scaling_curve(): Estimate scaling exponent from benchmark results
bootstrap_process_reliability(): Bootstrap ICC reliability by resampling participants
calibration_drift_profile(): Calibration drift profile across sessions/batches
calibration_error_model(): Build an empirical bivariate calibration-error model
data_quality_reporting_table(): Compact reporting table for eye-tracking data quality
effective_sampling_frequency(): Estimate effective sampling frequency from timestamps
estimate_calibration_error(): Estimate empirical calibration/validation error
eye_benchmark_design(): Define a computational benchmark design
find_process_measures(): Find process measures by channel, level, status, or text
gaze_data_quality_profile(): Empirical gaze data-quality profile
gaze_precision_rms_s2s(): Estimate RMS successive-sample gaze imprecision
gaze_uncertainty_ellipse(): Uncertainty ellipse implied by an empirical calibration-error model
inject_aoi_label_noise(): Inject AOI label noise
inject_calibration_offset(): Inject additive gaze calibration offset in coordinate units
inject_device_shift(): Inject an additive device/site shift in a numeric feature
inject_eye_missingness(): Inject generic missingness into selected columns
inject_pupil_dropout(): Inject pupil dropout
inject_sampling_jitter(): Inject timestamp jitter
inject_trial_imbalance(): Inject trial/row imbalance by dropping observations
measurement_error_budget(): Build a non-collapsed measurement-error budget
probabilistic_aoi_assignment(): Probabilistic AOI assignment under empirical calibration uncertainty
process_bland_altman(): Bland-Altman repeatability summary for two sessions
process_icc(): Absolute-agreement ICC(A,1) for repeated process measures
process_measure_card(): Return a one-measure process card
process_measure_guardrails(): Process-measure guardrail table
process_measure_lineage(): Process-measure lineage table
process_measure_registry(): Unified process-measure registry
process_measure_units(): List units used by registered process measures
process_null_benchmark(): Compare an observed effect against a negative-control null distribution
process_reliability_profile(): Test-retest process reliability profile
propagate_calibration_uncertainty(): Propagate empirical calibration uncertainty around gaze samples
register_process_measure(): Add a process measure to a registry without global mutation
run_eye_benchmark(): Run a computational scaling benchmark
split_half_process_reliability(): Split-half reliability for a trial-level process measure
stress_test_summary(): Summarise stress-test metrics
stress_tolerance_frontier(): Identify the empirical stress frontier for a metric
summarise_eye_benchmark(): Summarise benchmark timing and memory by problem size
synthetic_corruption_plan(): Define synthetic measurement corruptions for stress testing
validate_process_measure_registry(): Validate a process-measure registry

Reproducibility and software-paper evidence (0.9)

analysis_environment_snapshot(): Snapshot an eyeprocess analysis environment
audit_decision_provenance(): Audit decision provenance and completeness
export_prov_json(): Export lightweight PROV-oriented JSON
export_ro_crate_metadata(): Export minimal RO-Crate 1.3 metadata
eye_prov_graph(): Construct a lightweight provenance graph
eye_reproducibility_fingerprint(): Construct a reproducibility fingerprint
eye_session_manifest(): Create a session-level provenance manifest
file_hash_manifest(): Build a file hash manifest
freeze_software_paper_evidence(): Freeze software-paper evidence to an RDS with a hash
object_hash(): Hash an R object reproducibly within an R serialization version
paper_reproducibility_manifest(): Create a compact paper reproducibility manifest
provenance_edge_table(): Build a provenance edge table
provenance_lineage_table(): Build a provenance lineage node table
read_reproducibility_fingerprint(): Read a reproducibility fingerprint
software_paper_claim_matrix(): Create or normalize a software-paper claim matrix
software_paper_evidence_bundle(): Construct a software-paper evidence bundle
software_paper_gap_analysis(): Identify gaps in a software-paper evidence bundle
software_paper_readiness(): Descriptive software-paper readiness audit
validate_eye_prov_graph(): Validate a provenance graph
verify_reproducibility_fingerprint(): Verify an internally stored fingerprint hash
write_prov_dot(): Return Graphviz DOT for a provenance graph
write_reproducibility_fingerprint(): Write a reproducibility fingerprint
write_software_paper_evidence(): Write a human-readable software-paper evidence report

0.9 visualization and supporting utilities (0.9)

audit_eye_api(): Audit API lifecycle completeness and replacement contracts
fixation_boundary_uncertainty(): Distance to nearest rectangular AOI boundary
specification_curve_data(): Prepare ordered specification-curve data
validate_against_reference(): Compare a validation result with a frozen reference

Process IRT and validation reference (0.7)

Public process-aware IRT, semantic-validation, evidence-governance, simulation, recovery, transportability, and advanced measurement APIs introduced in the 0.7 development series.

algorithm_facet_effects(): Extract algorithm facet effects
as_irt_recovery_results(): Canonicalise parameter-recovery results
audit_bias(): Audit bias
audit_channel_incremental_information(): Audit out-of-sample incremental information from a process channel
audit_convergence(): Audit convergence and classified failures
audit_coverage(): Audit coverage
audit_distractor_attention(): Audit distractor attention patterns
audit_identifiability(): Audit empirical identifiability from replicate estimates
audit_interval_width(): Audit interval width
audit_irf_shape(): Audit item response-function shape departures
audit_latent_distribution(): Audit the empirical latent-trait distribution
audit_measurement_transportability(): Summarise measurement transportability across held-out groups
audit_process_adjusted_dif(): Audit DIF before and after process-data adjustment
audit_process_local_dependence(): Audit inter-option/process local dependence
audit_process_measurement_invariance(): Audit process measurement invariance across facets
audit_rmse(): Audit rmse
audit_sbc(): Audit SBC rank uniformity
calibration_transfer_audit(): Audit transfer of calibration across devices/sessions/sites
classify_item_missingness(): Classify item missingness using exposure and response evidence
compare_irt_models(): Compare multimodal IRT model objects
compare_latent_distribution_models(): Compare simple latent-distribution reference models
compare_parametric_nonparametric_irf(): Compare conventional logistic and flexible IRF shapes
compare_validation_engines(): Compare validation engines on common recovery output
compatibility_evidence_matrix(): Build a detailed compatibility evidence matrix
coordinate_fidelity_audit(): Coordinate semantic-fidelity audit
cross_device_process_equating_audit(): Cross-device process-scale equating audit
cross_version_adapter_regression(): Compare adapter output across software/format versions
detect_irt_changepoints(): Detect IRT/process change points using an SIC-inspired multichannel score
detect_process_changepoint(): Detect a response-process change point
device_facet_effects(): Extract device facet effects
distractor_process_map(): Build a distractor process map
encode_response_combinations(): Encode multiple-response item response combinations
equate_irt_scales(): Equate IRT scales using anchor item parameters
estimate_visual_exposure_probability(): Estimate visual exposure probability
event_roundtrip_audit(): Audit event survival across an interchange round trip
event_semantics_audit(): Audit event semantic preservation
expected_process_information(): Expected process-aware item utility under a theta distribution
explain_latent_interaction(): Explain local person-item latent-space interactions
external_validate_irt(): External validation on a completely held-out dataset
extract_parameter_truth(): Extract canonical parameter truth from simulated data
eye_stream_fidelity_audit(): Audit preservation of monocular/binocular stream semantics
facet_effects(): Extract facet effects from a many-facet process model
field_fidelity_report(): Field-level semantic fidelity report
fit_censored_normal_process_irt(): Conditional censored-normal calibration for bounded process measurements
fit_changepoint_multimodal_irt(): Fit a multimodal change-point IRT workflow
fit_changepoint_rt_irt(): Fit a change-point RT IRT workflow
fit_cognitive_diagnosis_process(): Cognitive-diagnosis model with process indicators
fit_continuous_time_irt(): Continuous-time IRT external-engine gate
fit_crossclassified_process_irt(): Cross-classified process IRT reference model
fit_dynamic_gpirt(): Dynamic GPIRT external-engine gate
fit_event_time_irt(): Fit an event-time IRT reference workflow
fit_flow_mirt(): Flow-MIRT external-engine gate
fit_gaze_informed_missingness_irt(): Fit a gaze-informed missingness IRT diagnostic
fit_gpirt(): GPIRT model-criticism interface
fit_irt_model(): Fit a registered multimodal IRT model
fit_joint_gaze_rt_irt(): Joint response, response-time, and gaze-process IRT
fit_joint_graded_rt_process_irt(): Joint graded-response, RT, and process reference model
fit_latent_class_process_irt(): Latent process-class IRT reference model
fit_latent_space_irt(): Fit a latent-space IRT model using LSMjml
fit_manyfacet_process_irt(): Many-facet process IRT reference model
fit_multimodal_trait_irt(): Multimodal trait-model convenience wrapper
fit_multiple_response_process_irt(): Fit a multiple-response process-IRT reference model
fit_nominal_gaze_irt(): Nominal/distractor IRT with option-level gaze
fit_omission_survival_irt(): Response/RT/omission survival IRT reference model
fit_process_hmm_irt(): Process-state HMM with an IRT response layer
fit_response_process_embedding_irt(): Fit an IRT response model augmented by sequence embeddings
fit_revisit_process_cdm(): Fit a revisiting-aware cognitive-diagnosis process workflow
fit_speed_accuracy_engagement_irt(): Speed-accuracy-engagement IRT convenience wrapper
fit_validation_replicate(): Fit one model-validation replicate
fit_variational_irt(): Variational IRT external-engine gate
generalizability_process_study(): Generalizability-style variance decomposition for a process measure
get_irt_model(): Retrieve a registered multimodal IRT model
grade_model_evidence(): Grade model evidence against an explicit validation contract
irt_compositional_channel(): Compositional AOI channel
irt_continuous_channel(): Continuous/bounded process channel for multimodal IRT
irt_count_channel(): Count-valued process channel for multimodal IRT
irt_functional_channel(): Functional trajectory channel
irt_model_spec(): Define a multimodal IRT model specification
irt_nominal_channel(): Nominal response/process channel
irt_response_channel(): Binary/ordinal response channel for multimodal IRT
irt_rt_channel(): Response-time channel for multimodal IRT
irt_sequence_channel(): Sequence/process-state channel
irt_survival_channel(): Survival/event-time channel for multimodal IRT
irt_validation_spec(): Specify a validation programme for a process-IRT model
latent_distribution_stress_test(): Stress-test IRT estimators across latent distributions
latent_trait_trajectory(): Estimate a descriptive continuous-time latent trajectory
leave_device_out_validation(): Leave device out validation
leave_item_out_validation(): Leave item out validation
leave_session_out_validation(): Leave session out validation
leave_site_out_validation(): Leave site out validation
list_irt_models(): List registered multimodal IRT models
negative_control_process_test(): Negative-control test for an allegedly informative process channel
option_process_information(): Quantify option-process information from a nominal gaze model
plot(<eye_adapter_regression_audit>): Plot eye adapter regression audit
plot(<eye_bids_roundtrip>): Plot eye bids roundtrip
plot(<eye_compatibility_evidence_matrix>): Plot detailed compatibility evidence
plot(<eye_event_roundtrip_audit>): Plot eye event roundtrip audit
plot(<eye_event_time_irt>): Plot eye event time irt
plot(<eye_gaze_informed_missingness_irt>): Plot eye gaze informed missingness irt
plot(<eye_gpirt>): Plot flexible IRF shape diagnostics
plot(<eye_incremental_information_audit>): Plot incremental process-channel information by fold
plot(<eye_irt_changepoints>): Plot detected process changepoints
plot(<eye_irt_equating>): Plot an IRT linking/equating transformation
plot(<eye_irt_ppc>): Plot posterior predictive discrepancy tail probabilities
plot(<eye_irt_recovery_summary>): Plot parameter-recovery bias or RMSE
plot(<eye_irt_sbc>): Plot SBC rank histograms by parameter
plot(<eye_joint_gaze_rt_irt>): Plot a joint gaze-response-time IRT fit
plot(<eye_joint_graded_rt_process_irt>): Plot a graded response + RT/process fit
plot(<eye_latent_distribution_comparison>): Plot eye latent distribution comparison
plot(<eye_latent_space_irt>): Plot a latent-space IRT adapter fit
plot(<eye_manyfacet_process_irt>): Plot many-facet process IRT effects
plot(<eye_nominal_gaze_irt>): Plot nominal-response gaze results
plot(<eye_omission_survival_irt>): Plot omission/not-reached survival IRT diagnostics
plot(<eye_process_cat_simulation>): Plot CAT simulation information accumulation
plot(<eye_process_channel_ablation>): Plot process-channel ablation
plot(<eye_process_dependent_discrimination>): Plot process-dependent discrimination
plot(<eye_process_facet_effects>): Plot eye process facet effects
plot(<eye_process_g_study>): Plot process-measure variance components
plot(<eye_process_hmm_irt>): Plot a process-HMM IRT fit
plot(<eye_process_local_dependence_audit>): Plot process/local-dependence diagnostics
plot(<eye_process_negative_control>): Plot a process-channel negative-control distribution
plot(<eye_process_person_fit>): Plot process person-fit discrepancies
plot(<eye_sbc_audit>): Plot SBC audit summaries
plot(<eye_semantic_roundtrip>): Plot semantic round-trip fidelity
plot(<eye_vendor_semantic_validation>): Plot eye vendor semantic validation
plot_distractor_information(): Plot option-level distractor information
plot_irf_uncertainty(): Plot uncertainty for flexible item response functions
plot_person_item_space(): Plot person/item latent-space coordinates
plot_process_changepoint(): Plot detected process change points
posterior_predictive_discrepancies(): Posterior predictive discrepancy table
posterior_sbc_contract(): Define a posterior-SBC replication contract
predict(<eye_censored_normal_process_irt>): Predict expected bounded response from a censored-normal process IRT fit
predict_theta_at_time(): Predict a latent trait at arbitrary times
print(<eye_irt_evidence_grade>): Print eye irt evidence grade
print(<eye_irt_model_spec>): Print a multimodal IRT model specification
print(<eye_irt_validation_spec>): Print eye irt validation spec
print(<eye_process_negative_control>): Print eye process negative control
print(<eye_vendor_schema_contract>): Print eye vendor schema contract
process_channel_ablation(): Ablate process channels under a common out-of-sample evaluator
process_dependent_discrimination_audit(): Audit process-dependent item discrimination
process_dif_nuisance_surrogate(): Construct a process-data nuisance surrogate for DIF analysis
process_item_information(): 2PL response item information
process_ngram_features(): N-gram features from process sequences
process_person_fit(): Joint response-process person-fit diagnostic
process_residual_map(): Return person/item latent-space coordinates
process_sequence_embedding(): Low-dimensional embedding of response-process sequences
process_state_occupancy(): Summarize HMM state occupancy
process_state_transition_summary(): Summarize HMM process-state transitions
promote_irt_model(): Promote an IRT model after evidence gates are met
public_validation_corpus(): Public validation-corpus registry
pupil_unit_fidelity_audit(): Pupil-unit semantic-fidelity audit
recalibrate_after_changepoint(): Iteratively detect, clean, and recalibrate after process change points
recommended_validation_replications(): Approximate simulation replications needed for a target Monte Carlo error
register_irt_model(): Register a multimodal IRT model
roundtrip_eye_bids(): Execute and audit an Eye-Tracking-BIDS round trip
run_posterior_sbc(): Run posterior simulation-based calibration from an explicit contract
run_sbc(): Run generic simulation-based calibration
select_next_item_process(): Select the next item using response/process utility
semantic_fidelity_spec(): Semantic fidelity specification
semantic_loss_map(): Convert a semantic round-trip audit into a loss map
semantic_roundtrip_audit(): Audit a complete semantic round trip
session_facet_effects(): Extract session facet effects
simulate_from_model(): Simulate data from a model or registered model specification
simulate_irt_model(): Simulate from a registered multimodal IRT model
simulate_process_cat(): Simulate a simple process-aware CAT policy
stress_test_latent_distribution(): Stress test latent distribution
stress_test_local_dependence(): Stress test local dependence
stress_test_missingness(): Stress test missingness
stress_test_misspecification(): Run a generic misspecification stress-test grid
stress_test_preprocessing(): Stress test preprocessing
stress_test_speededness(): Stress test speededness
summarize_parameter_recovery(): Summarise parameter recovery
timestamp_fidelity_audit(): Timestamp semantic-fidelity audit
validate_bids_eye_semantics(): Validate BIDS eye-tracking semantics
validate_hed_event_semantics(): Minimal HED annotation audit for event tables
validate_irt_model(): Validate a registered multimodal IRT model
validate_latent_space_process_similarity(): Validate latent-space proximity against process similarity
validate_vendor_semantics(): Validate imported data against a vendor semantic contract
validate_vendor_timestamp_semantics(): Validate vendor-specific timestamp semantics
validation_evidence_levels(): Detailed validation evidence levels
validation_failure_taxonomy(): Classify common estimator failures without hiding the original message
validation_mcse(): Monte Carlo standard errors for validation metrics
vendor_schema_contract(): Declare a vendor semantic schema contract

Package overview

eyeprocess eyeprocess-package: eyeprocess: Harmonize Eye-Tracking and Psychometric Process Data

Canonical data and adapters

eye_schema schema_table empty_eye_table standardize_eye_table validate_eye_table canonical_table_names new_coordinate_space: Canonical schemas and coordinate spaces
new_eye_dataset is_eye_dataset as_eye_dataset as_eye_dataset.eye_dataset as_eye_dataset.data.frame as_eye_dataset.default print.eye_dataset summary.eye_dataset print.summary.eye_dataset validate_eye_dataset print.eye_validation get_eye_table set_eye_table append_eye_table add_provenance provenance_manifest compact_eye_dataset: Create and manage eyeprocess datasets
eye_mapping print.eye_mapping validate_eye_mapping infer_eye_mapping register_eye_adapter unregister_eye_adapter supported_eye_formats detect_eye_format print.eye_format_detection read_eye_export read_eye_folder combine_eye_datasets remap_recording_ids: Mappings and adapter registry
read_eye_generic: Import generic delimited eye-tracking data

Gazepoint

is_gazepoint_export gp_identify_export_type gp_profile_export gp_list_export_fields gp_validate_export read_gazepoint read_gazepoint_gaze read_gazepoint_biometrics read_gazepoint_fixations read_gazepoint_events read_gazepoint_combined read_gazepoint_folder gp_pair_exports gp_match_recordings gp_match_biometrics gp_audit_file_pairs read_gazepoint_aoi_statistics read_gazepoint_summary gp_parse_user_events gp_parse_media_events gp_reconstruct_trials gp_reconstruct_stimuli gp_align_media_ids gp_parse_markers gp_check_sampling_rate gp_check_validity_fields gp_check_fixation_ids gp_check_media_timing gp_check_pupil_channels gp_check_biometrics_sync: Import Gazepoint and Gazepoint Biometrics exports
gazepoint_workflow_spec(): Specify an integrated Gazepoint downstream workflow
run_gazepoint_workflow(): Run the complete Gazepoint downstream workflow
build_gazepoint_media_trials(): Reconstruct media presentations as analysis trials
derive_gazepoint_workflow_features(): Derive the complete Gazepoint workflow feature set
gazepoint_analysis_tables(): Build person-by-item-by-trial analysis tables
gazepoint_irt_tables(): Create IRT-ready response and process tables
plot_gazepoint_workflow(): Generate the complete Gazepoint workflow plot suite
validate_gazepoint_workflow(): Validate an integrated Gazepoint workflow result
write_gazepoint_workflow_report(): Write a reproducible Gazepoint workflow report

Other vendors

is_tobii_export read_tobii is_pupil_labs_export pupil_labs_format read_pupillabs read_pupil_neon read_pupil_core is_eyelink_export read_eyelink_asc read_eyelink_report read_eyelink_edf is_smi_export read_smi read_smi_raw_export read_smi_event_export read_smi_aoi_export: Import Tobii, Pupil Labs, EyeLink, and SMI exports

Empirical format validation

format_validation_spec eye_format_profiles format_compatibility_matrix inspect_eye_source schema_coverage schema_coverage_summary source_preservation_audit fingerprint_eye_dataset compare_eye_datasets roundtrip_eye_dataset validate_eye_source validation_manifest write_validation_manifest read_validation_manifest discover_validation_cases init_validation_corpus validate_eye_corpus anonymize_eye_dataset write_format_validation_report create_validation_bundle validate_tobii_export validate_pupillabs_export validate_eyelink_export validate_smi_export validate_generic_export print.eye_format_validation_spec print.eye_roundtrip_validation print.eye_format_validation summary.eye_format_validation plot.eye_format_validation print.eye_corpus_validation plot.eye_corpus_validation: Validate real eye-tracking exports and compatibility corpora

Time, coordinates, trials, and AOIs

register_coordinate_space coordinate_space convert_xy convert_coordinates audit_coordinate_spaces estimate_sampling_rate normalize_timebase audit_timebase align_clock estimate_clock_transform print.eye_clock_transform apply_clock_transform synchronize_eye_biometrics audit_clock_sync: Coordinate and timebase management
build_trials build_stimulus_intervals assign_trials add_responses build_item_responses new_aoi print.eye_aoi register_aois assign_aois build_aoi_visits: Trials, responses, stimuli, and areas of interest

Preprocessing and features

preprocess_spec print.eye_preprocess_spec rolling_apply filter_gaze flag_gaze_outliers gaze_velocity interpolate_pupil filter_pupil baseline_pupil pupil_deconvolve detect_blinks detect_fixations_ivt detect_fixations_idt detect_saccades preprocess_eye: Gaze and pupil preprocessing
feature_spec print.eye_feature_spec trial_table summarize_fixations scanpath_sequence transition_matrix gaze_entropy transition_entropy derive_gaze_features derive_pupil_features derive_rt_features derive_biometric_features derive_all_features features_wide feature_dictionary: Derive gaze, pupil, response-time, and biometric features

Quality and governance

assign_aois_probabilistic() audit_aoi_separation() summarise_aoi_membership() propagate_aoi_uncertainty() plot_aoi_probability_map() plot_aoi_boundary_risk() plot_probabilistic_scanpath() plot_fuzzy_transition_matrix() plot_aoi_metric_uncertainty(): Probabilistic AOI assignment and uncertainty propagation
detect_calibration_drift() fit_offline_recalibration() apply_offline_recalibration() audit_recalibration() plot_calibration_vector_field() plot_calibration_error_ellipses() plot_drift_over_time() plot_recalibration_before_after() plot_screen_coverage(): Calibration drift and offline recalibration
fit_process_gstudy() process_variance_components() design_process_dstudy() audit_process_reliability() plot_variance_components() plot_dependability_surface() plot_reliability_by_metric() plot_session_stability() plot_item_sampling_reliability(): Process reliability and Generalizability Theory
fit_device_linking() apply_device_linking() audit_device_equivalence() estimate_device_specific_error() plot_device_agreement() plot_device_bias_by_magnitude() plot_device_transfer_curve() plot_device_equivalence_intervals() plot_cross_vendor_metric_matrix(): Cross-device and cross-vendor metric linking
register_pupil_curves() decompose_pupil_phase_amplitude() fit_phase_amplitude_irt() audit_pupil_registration() plot_pupil_registration() plot_warping_functions() plot_phase_amplitude_scores() plot_item_phase_delay() plot_registered_pupil_effects(): Pupil phase-amplitude registration
item_objective_spec() item_pareto_front() optimize_item_bank() audit_bank_decision_stability() plot_item_pareto() plot_objective_tradeoffs() plot_bank_information_coverage() plot_decision_stability() plot_selected_bank_profile(): Multi-objective item-bank optimization
fit_process_dif() monitor_dif_drift() decompose_dif_evidence() audit_fairness_transportability() plot_group_icc_process_overlay() plot_process_dif_forest() plot_dif_drift_heatmap() plot_fairness_transport_matrix() plot_item_group_process_curves(): Dynamic process-DIF and fairness drift
fit_process_norms() predict_process_centiles() score_process_deviation() audit_norm_transportability() plot_process_centiles() plot_normative_fan() plot_person_normative_profile() plot_item_normative_deviation(): Conditional process reference centiles
build_evidence_graph() trace_item_decision() compare_decision_provenance() audit_evidence_dependencies() plot_evidence_graph() plot_item_decision_path() plot_metric_dependency_graph() plot_model_decision_impact(): Evidence and decision provenance graphs
audit_3pl_process_signatures(): Identify items for descriptive 3PL/process review
audit_advanced_model_evidence(): Audit advanced-model scientific evidence
audit_benchmark_release(): Audit whether benchmark assets are ready for public release
audit_bias(): Audit bias
audit_biometric_imputation(): Alias emphasizing sensitivity rather than automatic replacement
audit_biometric_preflight(): Audit incoming biometric/process data before modelling
audit_candidate_item_bank(): Audit a candidate item bank against a seed model
audit_channel_incremental_information(): Audit out-of-sample incremental information from a process channel
audit_convergence(): Audit convergence and classified failures
audit_coverage(): Audit coverage
audit_decision_provenance(): Audit decision provenance and completeness
audit_distractor_attention(): Audit distractor attention patterns
audit_eye_api(): Audit API lifecycle completeness and replacement contracts
audit_eye_pipeline(): Audit a pipeline definition or completed run
audit_frontier_model_contract(): Audit whether a gated frontier model has a minimum evidence contract
audit_identifiability(): Audit empirical identifiability from replicate estimates
audit_interval_width(): Audit interval width
audit_irf_shape(): Audit item response-function shape departures
audit_item_reduction_sensitivity(): Run stepwise Rasch item-reduction as a sensitivity analysis
audit_latent_distribution(): Audit the empirical latent-trait distribution
audit_measurement_transportability(): Summarise measurement transportability across held-out groups
audit_model_promotion(): Audit promotion readiness for advanced model families
audit_multimodal_identifiability(): Audit basic multimodal design identifiability
audit_multimodal_m2_identifiability(): Audit structural and data identifiability for M0-M2
audit_multimodal_m3_identifiability(): Audit structural and measurement support for M3
audit_multimodal_m4_identifiability(): Audit M4 structural and posterior identifiability
audit_multimodal_measurement(): Audit a multimodal measurement object
audit_multivariate_process_quality(): Alias emphasizing data-quality interpretation of process anomaly auditing
audit_nonparametric_rasch(): Run nonparametric Rasch diagnostics with eRm
audit_presentation_accessibility(): Audit presentation/accessibility sensitivity without clinical inference
audit_process_adjusted_dif(): Audit DIF before and after process-data adjustment
audit_process_anomalies(): Audit multivariate process/data-quality anomalies
audit_process_drift(): Audit post-deployment psychometric and biometric drift
audit_process_external_validity(): Audit external/structural validity of process traits
audit_process_local_dependence(): Audit inter-option/process local dependence
audit_process_measurement_invariance(): Audit process measurement invariance across facets
audit_process_window_sensitivity(): Audit sensitivity of process summaries to temporal window choices
audit_pupil_fatigue_drift(): Audit within-person pupil fatigue/trial-order drift
audit_pupil_frequency_stability(): Audit stability of pupil frequency features across window lengths
audit_pupil_preprocessing_order(): Audit declared order of pupil preprocessing steps
audit_rmse(): Audit rmse
audit_roundtrip_loss(): Audit semantic and numerical loss after a round trip
audit_sampling_irregularity(): Audit sampling irregularity
audit_sbc(): Audit SBC rank uniformity
audit_signal_filter(): Summarize a signal-filter audit
audit_temporal_leakage(): Audit temporal leakage in a feature provenance table
audit_validation_completion(): Audit whether a validation programme is complete
audit_vendor_field_coverage(): Audit vendor field coverage against canonical semantics
audit_vendor_validation(): Audit a multi-vendor validation corpus
audit_visual_context_dependence(): Audit visual-context dependence
register_coordinate_space coordinate_space convert_xy convert_coordinates audit_coordinate_spaces estimate_sampling_rate normalize_timebase audit_timebase align_clock estimate_clock_transform print.eye_clock_transform apply_clock_transform synchronize_eye_biometrics audit_clock_sync: Coordinate and timebase management
store_quality audit_sampling_rate audit_signal_quality audit_pupil_quality audit_episodes audit_event_order audit_trial_coverage audit_aois audit_missingness check_process_leakage check_feature_level interpretive_warnings analysis_readiness print.eye_readiness compare_preprocessing compare_aoi_definitions sensitivity_process print.eye_sensitivity: Quality control, sensitivity, and governance
new_eye_dataset is_eye_dataset as_eye_dataset as_eye_dataset.eye_dataset as_eye_dataset.data.frame as_eye_dataset.default print.eye_dataset summary.eye_dataset print.summary.eye_dataset validate_eye_dataset print.eye_validation get_eye_table set_eye_table append_eye_table add_provenance provenance_manifest compact_eye_dataset: Create and manage eyeprocess datasets

Visualisation

eye_plot_spec() plot_diagnostics() plot_evidence() plot_sensitivity() autoplot_eyeprocess(): Measurement-intelligence plotting and result infrastructure
assign_aois_probabilistic() audit_aoi_separation() summarise_aoi_membership() propagate_aoi_uncertainty() plot_aoi_probability_map() plot_aoi_boundary_risk() plot_probabilistic_scanpath() plot_fuzzy_transition_matrix() plot_aoi_metric_uncertainty(): Probabilistic AOI assignment and uncertainty propagation
derive_aoi_composition() transform_aoi_composition() fit_aoi_compositional_model() compare_aoi_compositions() aoi_balance_coordinates() plot_aoi_ternary() plot_aoi_balance_biplot() plot_aoi_variation_matrix() plot_compositional_group_difference() plot_aoi_composition_trajectory(): Compositional analysis of AOI attention
process_uncertainty_spec() estimate_process_uncertainty() propagate_process_uncertainty() uncertainty_budget() compare_uncertainty_budgets() plot_uncertainty_waterfall() plot_uncertainty_tornado() plot_uncertainty_by_item() plot_uncertainty_by_stage(): Process measurement-uncertainty budgets
detect_calibration_drift() fit_offline_recalibration() apply_offline_recalibration() audit_recalibration() plot_calibration_vector_field() plot_calibration_error_ellipses() plot_drift_over_time() plot_recalibration_before_after() plot_screen_coverage(): Calibration drift and offline recalibration
fit_process_gstudy() process_variance_components() design_process_dstudy() audit_process_reliability() plot_variance_components() plot_dependability_surface() plot_reliability_by_metric() plot_session_stability() plot_item_sampling_reliability(): Process reliability and Generalizability Theory
fit_device_linking() apply_device_linking() audit_device_equivalence() estimate_device_specific_error() plot_device_agreement() plot_device_bias_by_magnitude() plot_device_transfer_curve() plot_device_equivalence_intervals() plot_cross_vendor_metric_matrix(): Cross-device and cross-vendor metric linking
register_pupil_curves() decompose_pupil_phase_amplitude() fit_phase_amplitude_irt() audit_pupil_registration() plot_pupil_registration() plot_warping_functions() plot_phase_amplitude_scores() plot_item_phase_delay() plot_registered_pupil_effects(): Pupil phase-amplitude registration
fit_process_observation_model() fit_joint_signal_missingness() process_pattern_mixture() sensitivity_mnar_process() plot_observation_probability() plot_missingness_by_time() plot_missingness_by_aoi() plot_mnar_tipping_point() plot_complete_case_sensitivity(): Informative missingness and MNAR sensitivity
gaze_recurrence() cross_recurrence() windowed_recurrence() recurrence_features() plot_recurrence_matrix() plot_windowed_recurrence() plot_diagonal_recurrence_profile() plot_crossmodal_recurrence() plot_recurrence_network(): Recurrence and cross-recurrence analysis
fit_fixation_point_process() fit_marked_gaze_process() predict_fixation_intensity() diagnose_gaze_point_process() plot_fixation_intensity() plot_spatial_residuals() plot_temporal_excitation_kernel() plot_covariate_effect_surface() plot_observed_expected_fixations(): Spatio-temporal fixation point-process models
representative_scanpath() scanpath_dispersion() compare_scanpath_distributions() bootstrap_representative_scanpath() plot_scanpath_atlas() plot_representative_scanpath() plot_scanpath_dispersion() plot_group_scanpath_transport() plot_scanpath_similarity_matrix(): Representative scanpaths and scanpath distributions
detect_process_changepoints() segment_process_episodes() label_process_episodes() compare_episode_structure() plot_process_episodes() plot_changepoint_ribbons() plot_episode_waterfall() plot_episode_transition_graph() plot_episode_duration_distribution(): Cognitive-episode change-point detection
item_objective_spec() item_pareto_front() optimize_item_bank() audit_bank_decision_stability() plot_item_pareto() plot_objective_tradeoffs() plot_bank_information_coverage() plot_decision_stability() plot_selected_bank_profile(): Multi-objective item-bank optimization
fit_process_dif() monitor_dif_drift() decompose_dif_evidence() audit_fairness_transportability() plot_group_icc_process_overlay() plot_process_dif_forest() plot_dif_drift_heatmap() plot_fairness_transport_matrix() plot_item_group_process_curves(): Dynamic process-DIF and fairness drift
fit_process_norms() predict_process_centiles() score_process_deviation() audit_norm_transportability() plot_process_centiles() plot_normative_fan() plot_person_normative_profile() plot_item_normative_deviation(): Conditional process reference centiles
build_evidence_graph() trace_item_decision() compare_decision_provenance() audit_evidence_dependencies() plot_evidence_graph() plot_item_decision_path() plot_metric_dependency_graph() plot_model_decision_impact(): Evidence and decision provenance graphs
plot.eye_dataset plot_eye_overview plot_eye_trace plot_fixations plot_scanpath plot_gaze_heatmap plot_aoi_dwell plot_transition_matrix plot_pupil_timeseries plot_biometrics plot_signal_quality plot_sampling_rate plot_missingness plot_trial_timeline plot_feature_distribution plot_feature_correlation plot_coordinate_spaces plot_clock_alignment plot_item_difficulty plot_model_diagnostics: Visualize eye-tracking and multimodal process data
plot_aoi_transition_matrix(): Plot an AOI transition matrix
plot_aoi_transition_rank(): Plot top AOI transitions by probability/count
plot_distractor_information(): Plot option-level distractor information
plot_gazepoint_workflow(): Generate the complete Gazepoint workflow plot suite
plot_interval_coverage(): Plot interval coverage
plot_irf_uncertainty(): Plot uncertainty for flexible item response functions
plot_parameter_recovery(): Plot parameter recovery
plot_person_item_space(): Plot person/item latent-space coordinates
plot_process_changepoint(): Plot detected process change points
plot_process_channel_ablation_delta(): Plot channel-ablation delta from a full/reference model
plot_process_feature_stability(): Plot process-feature stability across resamples/splits
plot_process_window_sensitivity(): Explicit wrapper for process-window sensitivity plotting
plot_pupil_activity_sensitivity(): Plot pupil activity sensitivity to window length
plot_pupil_activity_windows(): Plot pupil activity features across windows/groups
plot_pupil_band_power(): Plot pupil low/high-band power summaries
plot_pupil_components(): Plot tonic/phasic pupil components
plot_pupil_preprocessing_audit(): Plot raw-to-processed pupil preprocessing stages
plot_pupil_spectrum(): Plot a pupil-signal power spectrum
plot_sbc_rank(): Plot SBC rank histograms
plot_validation_failures(): Plot validation failure rates
plot_validation_runtime(): Plot validation runtime

Psychometrics

response_matrix response_time_matrix align_response_matrices model_data print.eyeprocess_model summary.eyeprocess_model print.summary.eyeprocess_model fit_irt fit_explanatory_irt fit_accuracy_rt print.eye_two_stage_rt fit_dif fit_shared_process_factor item_parameters person_scores model_fit_statistics predict.eyeprocess_model check_local_dependence fit_joint_process_model fit_dynamic_aoi_model print.eye_dynamic_aoi: Psychometric and process-data models
process_irt_spec print.process_irt_spec fit_process_irt fit_gaze_informed_irt fit_pupil_informed_irt fit_multimodal_irt process_irt_diagnostics functional_pupil_features fit_strategy_mixture print.eye_strategy_mixture estimate_ez_diffusion fit_gaze_weighted_choice model_missing_process sensitivity_missing_process print.eye_missing_sensitivity: Experimental psychometric process models

Interoperability and storage

eye_storage_spec(): Specify disk-backed eyeprocess storage
write_eye_storage(): Write an eye dataset to RDS or Arrow/Parquet storage
open_eye_storage(): Open an eyeprocess storage handle
collect_eye_storage(): Collect a disk-backed eye dataset
export_eye_bids(): Export Eye-Tracking-BIDS physiological recordings
import_eye_bids(): Import Eye-Tracking-BIDS physiological recordings
as_eyeprocess_eyetools() as_eyeprocess_eyetrackingr() as_eyeprocess_gazer() as_eyeprocess_eyeris() as_eyeprocess_pupillometryr(): Convert common external eye-tracking objects
as_procdata_sequence() as_traminer_sequence() as_seqhmm_data(): Convert scanpaths to process/sequence package contracts
fit_gdina_adapter(): fit gdina adapter
fit_diffirt_adapter(): Fit a diffusion IRT adapter
fit_openmx_process_model(): Fit a user-defined OpenMx process model

Validation programme

vendor_validation_spec(): Specify multi-vendor empirical validation requirements
audit_vendor_validation(): Audit a multi-vendor validation corpus
model_validation_spec(): Specify a model-validation programme
run_model_validation(): Run parameter-recovery, coverage, and misspecification validation
advanced_model_evidence_spec(): Specify evidence required to promote advanced model interfaces
audit_advanced_model_evidence(): Audit advanced-model scientific evidence
simulation_based_calibration(): Run simulation-based calibration
compare_model_engines(): Compare equivalent model engines
raven_reproduction_spec(): Specify a published Raven strategy-model reproduction
run_raven_reproduction(): Execute a licensed published-model reproduction
grouped_cv(): Evaluate a model with grouped cross-validation
crossed_grouped_cv(): Cross-classified grouped cross-validation
quantify_process_leakage(): Quantify leakage from row-wise rather than grouped validation
preprocessing_multiverse(): Run a preprocessing or AOI multiverse
benchmark_eyeprocess(): Benchmark an eyeprocess operation
reporting_guideline_audit(): Audit reporting-guideline coverage
write_reporting_guideline_report(): Write a reporting-guideline audit report
create_public_benchmark(): Create a public, de-identified benchmark bundle
write_software_paper_scaffold(): Write a methodological software-paper scaffold
run_eyeprocess_validation_program(): Run the complete validation-release programme

Advanced model programme

dynamic_irtree_spec(): Specify a hardened dynamic gaze-state IRTree
fit_dynamic_irtree(): Fit a dynamic gaze-state response-tree model
functional_pupil_irt_spec(): Specify a functional pupil-IRT model
fit_joint_functional_pupil_irt(): Fit a functional pupil-informed IRT workflow
theory_strategy_spec(): Define a theory-constrained strategy-mixture model
fit_theory_strategy_irt(): Fit a theory-constrained strategy mixture
gaze_diffusion_spec(): Define a gaze-informed diffusion model
fit_gaze_diffusion_irt(): Fit a gaze-informed diffusion model
advanced_validation_grid(): Construct the advanced-model validation grid
simulate_advanced_process_data(): Simulate advanced response-process data

Simulation and reporting

simulate_eye_dataset simulate_process_irt parameter_recovery summary.eye_parameter_recovery plot.eye_parameter_recovery power_process_simulation: Simulate and validate eyeprocess workflows
write_eye_dataset read_eye_dataset export_canonical import_canonical write_provenance report_eye_dataset report_processirt as_eye_dataset.gp3_recording as_eye_dataset.gp3_analysis as_eye_dataset.gp3_data as_eye_dataset.gpbiometrics_data as_eye_biometrics as_eye_biometrics.eye_dataset as_eye_biometrics.data.frame: Export, reporting, and package bridges

Validation evidence and reports

grouped_folds(): Create grouped cross-validation folds
crossed_grouped_folds(): Create cross-classified grouped folds
model_validation_summary(): Summarize model validation
sbc_summary(): Summarize simulation-based calibration
write_vendor_validation_report(): Write a multi-vendor validation report
write_advanced_model_evidence_report(): Write an advanced-model evidence report

Research-scale validation, models, storage, and reproducibility

Deterministic orchestration and explicitly gated advanced research infrastructure.

benchmark_expected_outputs(): Return expected benchmark outputs
benchmark_eye_storage(): Benchmark storage formats and query operations
build_compatibility_matrix(): Build the declared/fixture/empirical compatibility matrix
collect_validation_jobs(): Collect validation checkpoints from one or more directories
compare_diffusion_accuracy_rt(): Compare diffusion and conventional accuracy-RT models
compare_dynamic_transition_models(): Compare dynamic transition models
compare_engine_adapters(): Compare multiple external-engine adapter results
compare_functional_scalar_models(): Compare functional and scalar pupil summaries
compare_strategy_heterogeneity(): Compare mixture and continuous heterogeneity descriptions
compare_vendor_semantics(): Compare semantic mappings between vendors
decode_dynamic_states(): Decode latent or fitted transition states
detect_corrupt_partitions(): Detect missing, truncated, or modified partitions
diffusion_identification_study(): Construct a simulation-based identification study
diffusion_parameter_diagnostics(): Diagnose diffusion-parameter trade-offs and sampling
diffusion_posterior_predictive(): Posterior predictive summaries for accuracy and RT
dynamic_irtree_recovery(): Evaluate dynamic-state recovery under misclassification
dynamic_posterior_predictive_check(): Posterior predictive checks for dynamic state models
dynamic_transition_design(): Build an explicit dynamic-transition design matrix
engine_adapter_status(): Report an adapter's availability and contract
external_model_engines(): List external engine adapters
extract_diffusion_parameters(): Extract diffusion parameter summaries
extract_functional_pupil_parameters(): Extract functional pupil parameters for validation
eyeprocess_api_version(): Return the public eyeprocess API version
eyeprocess_benchmark_study(): Locate the bundled public benchmark study
eyeprocess_deprecation(): Declare a deprecation in a structured form
fingerprint_validation_case(): Fingerprint every file in a validation case
fit_brms_adapter(): fit brms adapter
fit_diffirt_engine_adapter(): fit diffirt engine adapter
fit_dynamic_irtree_stan(): Fit an optional CmdStan dynamic-transition model
fit_external_engine(): Fit an external model engine through a stable adapter
fit_eyetrackingr_adapter(): fit eyetrackingr adapter
fit_functional_pupil_stan(): Fit the bundled joint functional pupil-IRT Stan model
fit_gaze_diffusion_stan(): Fit the CmdStan Wiener diffusion model
fit_lnirt_adapter(): fit lnirt adapter
fit_mirt_adapter(): fit mirt adapter
fit_multinomial_transition(): Fit a penalized multinomial transition model
fit_openmx_adapter(): fit openmx adapter
fit_pupillometryr_adapter(): fit pupillometryr adapter
fit_seqhmm_adapter(): fit seqhmm adapter
fit_strategy_mixture_em(): Fit the deterministic multi-start EM baseline
fit_strategy_mixture_stan(): Fit the probabilistic strategy-mixture engine
fit_tam_adapter(): fit tam adapter
fit_traminer_adapter(): fit traminer adapter
functional_pupil_basis(): Construct a functional basis for pupil trajectories
functional_pupil_diagnostics(): Diagnose functional pupil model and preprocessing quality
import_benchmark_study(): Build an eye dataset from the public benchmark
init_vendor_corpus(): Create or validate a multi-vendor corpus directory
migrate_eye_storage_schema(): Migrate a storage schema through an atomic rewrite
model_promotion_spec(): Specify evidence gates for model promotion
object_schema(): Describe a stable object schema
open_partitioned_eye_storage(): Open partitioned eye storage
package_reproducibility_manifest(): Create a reproducibility manifest for files and software
partition_eye_storage(): Create a partition specification
plot(<eye_dynamic_irtree>): plot eye dynamic irtree
plot(<eye_dynamic_ppc>): plot eye dynamic ppc
plot(<eye_functional_pupil_diagnostics>): plot eye functional pupil diagnostics
plot(<eye_functional_pupil_irt>): plot eye functional pupil irt
plot(<eye_functional_pupil_sensitivity>): plot eye functional pupil sensitivity
plot(<eye_model_promotion_audit>): plot eye model promotion audit
plot(<eye_roundtrip_loss_audit>): plot eye roundtrip loss audit
plot(<eye_storage_benchmark>): plot eye storage benchmark
plot(<eye_strategy_aoi_sensitivity>): plot eye strategy aoi sensitivity
plot(<eye_transition_diagnostics>): plot eye transition diagnostics
plot(<eye_vendor_compatibility_matrix>): plot eye vendor compatibility matrix
predict(<eye_multinomial_transition>): Predict destination-state probabilities
prepare_dynamic_irtree_data(): Prepare ordered transition data for dynamic IRTree models
prepare_functional_pupil_data(): Prepare aligned, corrected functional pupil data
prepare_gaze_diffusion_data(): Prepare joint accuracy-response-time data
prepare_strategy_mixture_data(): Prepare data for a strategy-mixture model
print(<eye_benchmark_reproduction>): print eye benchmark reproduction
print(<eye_benchmark_study>): print eye benchmark study
print(<eye_benchmark_validation>): print eye benchmark validation
print(<eye_diffusion_diagnostics>): print eye diffusion diagnostics
print(<eye_diffusion_identification_study>): print eye diffusion identification study
print(<eye_dynamic_irtree>): print eye dynamic irtree
print(<eye_dynamic_ppc>): print eye dynamic ppc
print(<eye_dynamic_recovery>): print eye dynamic recovery
print(<eye_engine_adapter_result>): print eye engine adapter result
print(<eye_functional_pupil_data>): print eye functional pupil data
print(<eye_functional_pupil_diagnostics>): print eye functional pupil diagnostics
print(<eye_functional_pupil_irt>): print eye functional pupil irt
print(<eye_functional_pupil_sensitivity>): print eye functional pupil sensitivity
print(<eye_functional_scalar_comparison>): print eye functional scalar comparison
print(<eye_gaze_diffusion_data>): print eye gaze diffusion data
print(<eye_gaze_diffusion_irt>): print eye gaze diffusion irt
print(<eye_gaze_diffusion_spec>): print eye gaze diffusion spec
print(<eye_model_contract_validation>): print eye model contract validation
print(<eye_model_promotion_audit>): print eye model promotion audit
print(<eye_multinomial_transition>): print eye multinomial transition
print(<eye_partition_spec>): print eye partition spec
print(<eye_partitioned_storage>): print eye partitioned storage
print(<eye_redaction_result>): print eye redaction result
print(<eye_roundtrip_loss_audit>): print eye roundtrip loss audit
print(<eye_strategy_data>): print eye strategy data
print(<eye_strategy_manipulation_validation>): print eye strategy manipulation validation
print(<eye_theory_strategy_irt>): print eye theory strategy irt
print(<eye_theory_strategy_spec>): print eye theory strategy spec
print(<eye_transition_design>): print eye transition design
print(<eye_transition_diagnostics>): print eye transition diagnostics
print(<eye_validation_case_fingerprint>): print eye validation case fingerprint
print(<eye_validation_collection>): print eye validation collection
print(<eye_validation_completion_audit>): print eye validation completion audit
print(<eye_validation_job_plan>): print eye validation job plan
print(<eye_validation_run>): print eye validation run
print(<eye_vendor_case>): print eye vendor case
print(<eye_vendor_compatibility_matrix>): print eye vendor compatibility matrix
print(<eye_vendor_semantic_comparison>): print eye vendor semantic comparison
promote_vendor_support(): Promote a case support level only when evidence is supplied
prune_validation_checkpoints(): Remove obsolete or corrupt validation checkpoints
pupil_preprocessing_grid(): Create a preprocessing sensitivity grid for pupil analysis
pupil_preprocessing_sensitivity(): Run functional pupil preprocessing sensitivity analysis
query_eye_storage(): Query partitioned eye storage lazily where possible
read_benchmark_table(): Read a benchmark table
read_validation_job_manifest(): Read a validation manifest
read_vendor_registry(): Read the multi-vendor case registry
redact_validation_case(): Redact a validation case without inventing replacement data
register_validation_case(): Register an independent validation case
register_vendor_semantics(): Register vendor-field semantics
resume_validation_jobs(): Resume incomplete or failed validation jobs
run_benchmark_reproduction(): Derive reproducible benchmark summaries
run_validation_jobs(): Run validation jobs with checkpointing and deterministic seeds
simulate_dynamic_irtree_data(): Simulate observed dynamic-state transitions
simulate_gaze_diffusion_data(): Simulate a hierarchical gaze-diffusion study
simulate_strategy_mixture_data(): Simulate a theory-defined strategy-mixture study
split_validation_plan(): Split a validation plan into independent chunks
storage_transaction_manifest(): Return the transaction manifest
strategy_aoi_sensitivity(): Assess sensitivity to alternative AOI feature definitions
strategy_classification_uncertainty(): Quantify strategy-classification uncertainty
strategy_label_switching_diagnostics(): Diagnose label stability across multiple starts
strategy_posterior_probabilities(): Posterior strategy probabilities
structural_transition_mask(): Define structural-zero and allowed transition masks
summary(<eye_validation_job_plan>): summary eye validation job plan
transition_residual_diagnostics(): Compute transition residual diagnostics
upgrade_eye_dataset(): Upgrade a legacy eye dataset
upgrade_eyeprocess_model(): Upgrade a legacy eyeprocess model
validate_benchmark_study(): Validate benchmark integrity and relational constraints
validate_engine_adapter(): Validate an external-engine adapter contract
validate_eye_storage_metadata(): Validate storage metadata and partition fingerprints
validate_model_object(): Validate a fitted model against the stable model contract
validate_strategy_manipulation(): Validate strategy posteriors against an experimental manipulation
validation_calibration_summary(): Summarize prediction calibration
validation_failure_summary(): Summarize convergence and execution failures
validation_job_plan(): Create a deterministic validation job plan
validation_recovery_summary(): Summarize parameter recovery
validation_runtime_summary(): Summarize validation runtime and checkpoint scale
validation_sbc_summary(): Summarize simulation-based calibration ranks
validation_seed(): Allocate a deterministic validation seed
validation_thresholds(): Specify completion and scientific-promotion thresholds
verify_reproducibility_manifest(): Verify a reproducibility manifest
write_benchmark_data_dictionary(): Write the benchmark data dictionary
write_model_promotion_report(): Write a model-promotion report
write_partitioned_eye_storage(): Write an eye dataset as atomic partitioned storage
write_software_paper_reproduction(): Write a complete software-paper reproduction scaffold
write_validation_job_manifest(): Write a machine-readable validation manifest
write_validation_release_report(): Write a validation release report
write_vendor_case_report(): Write a vendor case evidence report
write_vendor_registry(): Write the multi-vendor case registry

Measurement intelligence, uncertainty, transportability, and decision evidence

Reference implementations with explicit uncertainty, validation, and interpretation boundaries.

derive_aoi_composition() transform_aoi_composition() fit_aoi_compositional_model() compare_aoi_compositions() aoi_balance_coordinates() plot_aoi_ternary() plot_aoi_balance_biplot() plot_aoi_variation_matrix() plot_compositional_group_difference() plot_aoi_composition_trajectory(): Compositional analysis of AOI attention
fit_device_linking() apply_device_linking() audit_device_equivalence() estimate_device_specific_error() plot_device_agreement() plot_device_bias_by_magnitude() plot_device_transfer_curve() plot_device_equivalence_intervals() plot_cross_vendor_metric_matrix(): Cross-device and cross-vendor metric linking
detect_calibration_drift() fit_offline_recalibration() apply_offline_recalibration() audit_recalibration() plot_calibration_vector_field() plot_calibration_error_ellipses() plot_drift_over_time() plot_recalibration_before_after() plot_screen_coverage(): Calibration drift and offline recalibration
assign_aois_probabilistic() audit_aoi_separation() summarise_aoi_membership() propagate_aoi_uncertainty() plot_aoi_probability_map() plot_aoi_boundary_risk() plot_probabilistic_scanpath() plot_fuzzy_transition_matrix() plot_aoi_metric_uncertainty(): Probabilistic AOI assignment and uncertainty propagation
eye_plot_spec() plot_diagnostics() plot_evidence() plot_sensitivity() autoplot_eyeprocess(): Measurement-intelligence plotting and result infrastructure
representative_scanpath() scanpath_dispersion() compare_scanpath_distributions() bootstrap_representative_scanpath() plot_scanpath_atlas() plot_representative_scanpath() plot_scanpath_dispersion() plot_group_scanpath_transport() plot_scanpath_similarity_matrix(): Representative scanpaths and scanpath distributions
build_evidence_graph() trace_item_decision() compare_decision_provenance() audit_evidence_dependencies() plot_evidence_graph() plot_item_decision_path() plot_metric_dependency_graph() plot_model_decision_impact(): Evidence and decision provenance graphs
detect_process_changepoints() segment_process_episodes() label_process_episodes() compare_episode_structure() plot_process_episodes() plot_changepoint_ribbons() plot_episode_waterfall() plot_episode_transition_graph() plot_episode_duration_distribution(): Cognitive-episode change-point detection
process_uncertainty_spec() estimate_process_uncertainty() propagate_process_uncertainty() uncertainty_budget() compare_uncertainty_budgets() plot_uncertainty_waterfall() plot_uncertainty_tornado() plot_uncertainty_by_item() plot_uncertainty_by_stage(): Process measurement-uncertainty budgets
gaze_recurrence() cross_recurrence() windowed_recurrence() recurrence_features() plot_recurrence_matrix() plot_windowed_recurrence() plot_diagonal_recurrence_profile() plot_crossmodal_recurrence() plot_recurrence_network(): Recurrence and cross-recurrence analysis
fit_process_missingness_model() crossmodal_recurrence_model(): Measurement-intelligence compatibility adapters
fit_process_dif() monitor_dif_drift() decompose_dif_evidence() audit_fairness_transportability() plot_group_icc_process_overlay() plot_process_dif_forest() plot_dif_drift_heatmap() plot_fairness_transport_matrix() plot_item_group_process_curves(): Dynamic process-DIF and fairness drift
register_pupil_curves() decompose_pupil_phase_amplitude() fit_phase_amplitude_irt() audit_pupil_registration() plot_pupil_registration() plot_warping_functions() plot_phase_amplitude_scores() plot_item_phase_delay() plot_registered_pupil_effects(): Pupil phase-amplitude registration
fit_process_gstudy() process_variance_components() design_process_dstudy() audit_process_reliability() plot_variance_components() plot_dependability_surface() plot_reliability_by_metric() plot_session_stability() plot_item_sampling_reliability(): Process reliability and Generalizability Theory
fit_fixation_point_process() fit_marked_gaze_process() predict_fixation_intensity() diagnose_gaze_point_process() plot_fixation_intensity() plot_spatial_residuals() plot_temporal_excitation_kernel() plot_covariate_effect_surface() plot_observed_expected_fixations(): Spatio-temporal fixation point-process models
fit_process_observation_model() fit_joint_signal_missingness() process_pattern_mixture() sensitivity_mnar_process() plot_observation_probability() plot_missingness_by_time() plot_missingness_by_aoi() plot_mnar_tipping_point() plot_complete_case_sensitivity(): Informative missingness and MNAR sensitivity
fit_process_norms() predict_process_centiles() score_process_deviation() audit_norm_transportability() plot_process_centiles() plot_normative_fan() plot_person_normative_profile() plot_item_normative_deviation(): Conditional process reference centiles
item_objective_spec() item_pareto_front() optimize_item_bank() audit_bank_decision_stability() plot_item_pareto() plot_objective_tradeoffs() plot_bank_information_coverage() plot_decision_stability() plot_selected_bank_profile(): Multi-objective item-bank optimization

Process measurement and deployment governance reference (0.8)

Public 0.8 APIs for process pre-flight, deployment drift, temporal and pupil representations, contextual and mixture IRT, exploratory structure, external validity, Bayesian/3PL diagnostics, streaming scoring, sensitivity analysis, validation reporting, and gated frontier methods.

addm_glam_proxy_features(): Compute aDDM/GLAM-inspired gaze-evidence proxy features
adjust_pupil_confounds(): Extract confound-adjusted pupil values
aoi_trajectory_features(): Extract AOI growth-curve/trajectory features
apply_preflight_decision(): Apply a pre-flight decision to data explicitly
assign_process_feature_family(): Assign features to conservative process-feature families
audit_3pl_process_signatures(): Identify items for descriptive 3PL/process review
audit_biometric_imputation(): Alias emphasizing sensitivity rather than automatic replacement
audit_biometric_preflight(): Audit incoming biometric/process data before modelling
audit_candidate_item_bank(): Audit a candidate item bank against a seed model
audit_frontier_model_contract(): Audit whether a gated frontier model has a minimum evidence contract
audit_item_reduction_sensitivity(): Run stepwise Rasch item-reduction as a sensitivity analysis
audit_multivariate_process_quality(): Alias emphasizing data-quality interpretation of process anomaly auditing
audit_nonparametric_rasch(): Run nonparametric Rasch diagnostics with eRm
audit_presentation_accessibility(): Audit presentation/accessibility sensitivity without clinical inference
audit_process_anomalies(): Audit multivariate process/data-quality anomalies
audit_process_drift(): Audit post-deployment psychometric and biometric drift
audit_process_external_validity(): Audit external/structural validity of process traits
audit_process_window_sensitivity(): Audit sensitivity of process summaries to temporal window choices
audit_pupil_fatigue_drift(): Audit within-person pupil fatigue/trial-order drift
audit_pupil_frequency_stability(): Audit stability of pupil frequency features across window lengths
audit_signal_filter(): Summarize a signal-filter audit
audit_visual_context_dependence(): Audit visual-context dependence
bayesian_process_diagnostic_flags(): Extract compact Bayesian process-model diagnostic flags
bayesian_process_diagnostics_dashboard(): Summarize Bayesian process-model diagnostics
bind_process_windows(): Bind compatible process-window objects
biometric_imputation_sensitivity(): Run biometric-feature imputation as a sensitivity analysis
collect_validation_evidence(): Collect validation evidence into a common bundle
compare_aoi_trajectories(): Compare AOI trajectory feature objects
compare_bayesian_process_models(): Compare Bayesian process models by LOO or Bayes factor
compare_deployment_batches(): Compare two deployment batches descriptively
compare_presentation_fairness(): Compare outcomes across presentation variants
compare_process_criterion_models(): Compare process external-validity models
compare_process_profile_solutions(): Compare candidate process-profile solutions
compare_pupil_kernels(): Compare pupil deconvolution kernels
compare_raw_adjusted_pupil(): Compare raw and confound-adjusted pupil values
compare_signal_filters(): Compare multiple signal filters
compare_visual_context_irt(): Compare base and visual-context IRT models
context_factor_effects(): Extract visual-context factor effects/loadings
drift_by_device(): Drift audit stratified by device
drift_by_site(): Drift audit stratified by study site
drift_by_stimulus_version(): Drift audit stratified by stimulus version
drift_by_vendor(): Drift audit stratified by vendor
export_validation_bundle(): Export a validation evidence bundle
extract_process_windows(): Extract standardized sliding-window process features
filter_eye_signal(): Filter a one-dimensional eye signal robustly
filter_pupil_signal(): Filter pupil signal robustly
fit_aoi_growth_curve(): Fit a single AOI growth curve
fit_crossclassified_process_irt_mhrm(): Create a gated scalable cross-classified MH-RM process IRT interface
fit_gaze_anchored_3pl_audit(): Fit a standard 3PL and audit lower-asymptote alignment with process evidence
fit_item_parameter_seed_model(): Fit an experimental pre-pilot item-parameter seeding model
fit_kde_latent_distribution_irt(): Create a gated KDE latent-distribution IRT interface
fit_mixture_irt_process_classes(): Fit a true mirt mixture-IRT response model
fit_multiblock_process_map(): Fit a multiblock psychometric/gaze/pupil/quality structure map
fit_nonignorable_missing_irt(): Create a gated Bayesian nonignorable-missing IRT interface
fit_persistence_gaze_diffusion_irt(): Create a gated persistence-augmented gaze-diffusion IRT interface
fit_process_profile_mixture(): Fit exploratory process profiles
fit_process_rasch_tree(): Fit a process-informed Rasch tree
fit_pupil_confound_model(): Fit a luminance/fatigue/process confound model for pupil response
fit_pupil_event_deconvolution(): Fit transparent event-related pupil deconvolution models
fit_visual_context_irt(): Fit an explicit visual-context/testlet IRT model
gaze_anchored_3pl_alignment(): Return the process-alignment table from a gaze-anchored 3PL audit
incremental_process_validity(): Extract incremental process validity
map_latent_classes_to_process_profiles(): Map supplied latent-class memberships to process summaries
multiblock_contributions(): Extract multiblock block contributions/coordinates
multiblock_person_coordinates(): Extract multiblock person coordinates
multiblock_variable_coordinates(): Extract multiblock variable coordinates
plot(<eye_aoi_growth_curve>): Plot aoi growth curve diagnostics
plot(<eye_aoi_trajectory>): Plot aoi trajectory diagnostics
plot(<eye_bayesian_process_dashboard>): Plot bayesian process dashboard diagnostics
plot(<eye_biometric_imputation_sensitivity>): Plot biometric imputation sensitivity diagnostics
plot(<eye_biometric_preflight>): Plot biometric preflight diagnostics
plot(<eye_candidate_item_bank_audit>): Plot candidate item bank audit diagnostics
plot(<eye_decision_process_proxy>): Plot decision process proxy diagnostics
plot(<eye_gated_process_model>): Plot gated process model diagnostics
plot(<eye_gaze_anchored_3pl_audit>): Plot gaze anchored 3pl audit diagnostics
plot(<eye_item_parameter_seed>): Plot item parameter seed diagnostics
plot(<eye_item_reduction_sensitivity>): Plot item reduction sensitivity diagnostics
plot(<eye_latent_process_alignment>): Plot latent process alignment diagnostics
plot(<eye_mixture_irt_process>): Plot mixture irt process diagnostics
plot(<eye_multiblock_process_map>): Plot multiblock process map diagnostics
plot(<eye_nonparametric_rasch_audit>): Plot nonparametric rasch audit diagnostics
plot(<eye_preaction_process_features>): Plot preaction process features diagnostics
plot(<eye_presentation_accessibility>): Plot presentation accessibility diagnostics
plot(<eye_presentation_fairness_comparison>): Plot presentation fairness comparison diagnostics
plot(<eye_process_anomaly_audit>): Plot process anomaly audit diagnostics
plot(<eye_process_drift_audit>): Plot process drift audit diagnostics
plot(<eye_process_external_validity>): Plot process external validity diagnostics
plot(<eye_process_feature_blocks>): Plot process feature blocks diagnostics
plot(<eye_process_profile_mixture>): Plot process profile mixture diagnostics
plot(<eye_process_rasch_tree>): Plot process rasch tree diagnostics
plot(<eye_process_window_sensitivity>): Plot process window sensitivity diagnostics
plot(<eye_process_windows>): Plot process windows diagnostics
plot(<eye_pupil_confound_model>): Plot pupil confound model diagnostics
plot(<eye_pupil_deconvolution>): Plot pupil deconvolution diagnostics
plot(<eye_pupil_fatigue_drift>): Plot pupil fatigue drift diagnostics
plot(<eye_pupil_frequency_features>): Plot pupil frequency features diagnostics
plot(<eye_pupil_frequency_stability>): Plot pupil frequency stability diagnostics
plot(<eye_signal_filter_audit>): Plot signal filter audit diagnostics
plot(<eye_streaming_score>): Plot streaming score diagnostics
plot(<eye_validation_bundle>): Plot validation bundle diagnostics
plot(<eye_visual_context_irt>): Plot visual context irt diagnostics
plot_aoi_transition_matrix(): Plot an AOI transition matrix
plot_aoi_transition_rank(): Plot top AOI transitions by probability/count
plot_process_channel_ablation_delta(): Plot channel-ablation delta from a full/reference model
plot_process_feature_stability(): Plot process-feature stability across resamples/splits
plot_process_window_sensitivity(): Explicit wrapper for process-window sensitivity plotting
plot_pupil_activity_sensitivity(): Plot pupil activity sensitivity to window length
plot_pupil_activity_windows(): Plot pupil activity features across windows/groups
plot_pupil_band_power(): Plot pupil low/high-band power summaries
plot_pupil_components(): Plot tonic/phasic pupil components
plot_pupil_preprocessing_audit(): Plot raw-to-processed pupil preprocessing stages
plot_pupil_spectrum(): Plot a pupil-signal power spectrum
preaction_process_features(): Build pre-action process features
predict_aoi_trajectory(): Predict from an AOI growth curve
predict_item_parameter_priors(): Predict pre-pilot item-parameter priors
preflight_decisions(): Extract pre-flight decisions
preflight_exclusion_manifest(): Create an explicit pre-flight exclusion/review manifest
preflight_failures(): Extract pre-flight failures/review cases
preflight_passed(): Extract pre-flight passes
prepare_structured_unstructured_process_features(): Prepare leakage-safe structured/unstructured process representations
print(<eye_gated_process_model>): Print a gated process model object
print(<eye_process_drift_spec>): Print a process drift spec object
print(<eye_process_preflight_spec>): Print a process preflight spec object
print(<eye_process_window_spec>): Print a process window spec object
print(<eye_validation_bundle>): Print a validation bundle object
print(<eye_visual_context_registry>): Print a visual context registry object
process_anomaly_distance(): Extract multivariate process anomaly distances
process_criterion_associations(): Extract process-criterion associations
process_drift_alerts(): Extract drift alerts
process_drift_spec(): Specify a process-deployment drift audit
process_feature_blocks(): Define conceptual process-feature blocks
process_feature_family_registry(): Registry of process-feature families and interpretation guardrails
process_feature_stability(): Summarize process-feature stability across repeated analyses
process_preflight_spec(): Specify a biometric process pre-flight gate
process_profile_probabilities(): Extract process-profile probabilities
process_profile_summary(): Summarize process profiles
process_window_spec(): Specify temporal process windows
pupil_activity_index(): Compute a transparent pupil activity index
pupil_band_power(): Compute pupil signal power in a frequency band
pupil_confound_effects(): Extract pupil confound-model effects
pupil_event_effects(): Extract event effects from pupil deconvolution
pupil_event_regressor(): Build an event-locked pupil regressor
pupil_frequency_features(): Extract pupil frequency-domain and activity features by group
pupil_response_kernel(): Canonical gamma-shaped pupil response kernel
pupil_velocity_activity(): Derivative-based pupil activity magnitude
score_partial_response_pattern(): Score a partial response pattern from a calibrated mirt model
score_response_stream(): Score a response stream cumulatively
simulate_presentation_variants(): Simulate pre-registered presentation variants for review
streaming_score_history(): Extract streaming score history
summarize_process_windows(): Summarize extracted process windows
summary(<eye_validation_bundle>): Summarize a validation bundle object
update_person_score(): Update a partial person score with one new response
validate_process_windows(): Validate a process-window representation
validation_bundle_manifest(): Create a machine-readable validation manifest
validation_report(): Render a conservative validation report
visual_context_registry(): Build an item-to-visual-context registry
write_validation_report(): Write a validation report to disk

Multimodal Process-IRT (0.10 development)

Canonical multimodal measurement, process-information, simulation, and validation interfaces.

ablate_multimodal_channels(): Create formal channel-ablation datasets
multimodal_backend_status(): Report multimodal backend availability
multimodal_irt_spec(): Consolidated multimodal IRT specification
multimodal_ppc(): Posterior predictive checks for multimodal development fits
prepare_multimodal_irt_data(): Prepare a canonical multimodal person-item-trial measurement object
process_information(): Quantify incremental process information
simulate_multimodal_irt(): Simulate multimodal IRT process data
validate_multimodal_irt(): Validate a multimodal IRT development object

0.10 M2 response + RT + gaze evidence

fit_multimodal_m2(): Fit the M2 response + RT + gaze reference model
multimodal_m2_ablation(): Fit M0, M1, and M2 as a response-target ablation sequence
multimodal_m2_negative_controls(): Generate M2 alignment negative controls
multimodal_m2_ppc(): Posterior predictive checks for the M2 three-way model
multimodal_m2_process_information(): Quantify response-target process information in the M0-M2 sequence
multimodal_m2_recovery(): Run repeated M2 estimator recovery
multimodal_m2_spec(): M2 response + RT + gaze reference specification
simulate_multimodal_m2(): Simulate from the M2 response + RT + gaze generative model
validate_multimodal_m2(): Validate an M2 fit or simulation

0.10 M3 response + RT + gaze + pupil

Experimental/gated four-channel multimodal measurement, simulation, fitting, diagnostics, falsification, recovery, ablation, and information assessment.

audit_multimodal_m3_identifiability(): Audit structural and measurement support for M3
fit_multimodal_m3(): Fit the M3 response + RT + gaze + pupil reference model
multimodal_m3_ablation(): Fit the complete M3 response-anchored channel-ablation lattice
multimodal_m3_functional_bridge(): Bridge existing functional pupil outputs into the scalar M3 reference layer
multimodal_m3_negative_controls(): Generate M3 multimodal falsification controls
multimodal_m3_ppc(): Posterior predictive checks for the M3 four-channel model
multimodal_m3_process_information(): Quantify M3 process information, pupil increment, redundancy and sensor value
multimodal_m3_recovery(): Run M3 parameter-recovery and stress evidence
multimodal_m3_spec(): M3 response + RT + gaze + pupil specification
simulate_multimodal_m3(): Simulate the M3 response + RT + gaze + pupil generative model
validate_multimodal_m3(): Validate an M3 simulation or fitted four-channel model

0.11 M4 latent response-process states

audit_multimodal_m4_identifiability(): Audit M4 structural and posterior identifiability
fit_multimodal_m4(): Fit the M4 latent response-process state model
multimodal_m4_ablation(): Plan or fit the focused M3-to-M4 ablation set
multimodal_m4_negative_controls(): Construct M4 temporal, nuisance, device, and overfitting negative controls
multimodal_m4_ppc(): Posterior predictive checks for M4 measurement and sequential behavior
multimodal_m4_process_information(): Quantify incremental response-target information supplied by M4 state structure
multimodal_m4_recovery(): Evaluate deterministic M4 parameter and state recovery
multimodal_m4_sensitivity(): Plan or run M4 state-count and modelling sensitivity analyses
multimodal_m4_spec(): Specify M4 trait-conditioned latent response-process states
multimodal_m4_state_diagnostics(): Summarize M4 latent-state uncertainty and dynamics
simulate_multimodal_m4(): Simulate M4 multimodal sequential measurement data
validate_multimodal_m4(): Validate M4 data, computation, state behavior, and evidence