Package: sandtablR 0.0.0.9000

Raban Heller

sandtablR: Mass-Casualty Incident Simulation and Machine Learning Workbench

A generic framework for mass-casualty incident tabletop exercise simulation, decision-path analysis, and machine learning. Provides a discrete-event patient-flow engine, a tidy data model for scenarios, patient cards and decision paths, synthetic cohort generation, supervised triage and therapy-concept classification spanning interpretable and black-box models, sequence analysis of participant decision paths, and a model-agnostic explainability layer. An interactive 'shiny' workbench ties the pieces together for scenario building, simulation, model training, comparison and visualisation.

Authors:Raban Heller [aut, cre], Gerhard Achatz [aut]

sandtablR_0.0.0.9000.tar.gz
sandtablR_0.0.0.9000.zip(r-4.7-any)sandtablR_0.0.0.9000.zip(r-4.6-any)sandtablR_0.0.0.9000.zip(r-4.5-any)
sandtablR_0.0.0.9000.tgz(r-4.6-any)sandtablR_0.0.0.9000.tgz(r-4.5-any)
sandtablR_0.0.0.9000.tar.gz(r-4.7-any)sandtablR_0.0.0.9000.tar.gz(r-4.6-any)
sandtablR_0.0.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sandtablR/json (API)

# Install 'sandtablR' in R:
install.packages('sandtablR', repos = c('https://cttir.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cttir/sandtablr/issues

Pkgdown/docs site:https://cttir.github.io

On CRAN:

Conda:

3.60 score 70 exports 28 dependencies

Last updated from:39ff683492. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK535
source / vignettesOK331
linux-releaseOK489
macos-releaseOK525
macos-oldrelOK387
windows-develOK537
windows-releaseOK504
windows-oldrelOK488
wasm-releaseOK182

Exports:sdt_add_decisionssdt_appsdt_app_serversdt_app_uisdt_apply_gold_standardsdt_area_labelssdt_as_patient_cardssdt_board_areassdt_cohortsdt_consistency_scoresdt_course_compositionsdt_decision_consistencysdt_decision_pathssdt_describesdt_describe_participantssdt_describe_rendersdt_diagnosticssdt_enginessdt_error_fidelitysdt_explainsdt_export_simulationsdt_fidelitysdt_fitsdt_fit_behavioursdt_fit_triage_errorsdt_importancesdt_injury_regionssdt_life_rangesdt_metric_setsdt_metricssdt_participant_dictionarysdt_participant_summarysdt_patient_cardsdt_plot_boardsdt_plot_end_statesdt_plot_fidelitysdt_plot_flowsdt_plot_sequencessdt_plot_triage_mixsdt_plot_utilisationsdt_predictionssdt_profilesdt_read_gold_standardsdt_read_participantssdt_referencesdt_reference_horizonsdt_reference_scenariosdt_rocsdt_run_appsdt_run_behavioursdt_scenariosdt_seq_clustersdt_seqdefsdt_sex_levelssdt_shapsdt_simulatesdt_simulate_groupssdt_simulate_triagesdt_synthesis_utilitysdt_synthesisesdt_synthetic_cohortsdt_therapy_levelssdt_transformersdt_transformer_fitsdt_transformer_predictsdt_triage_accuracysdt_triage_levelssdt_workflowsetvalidate_cohortvalidate_patient_card

Dependencies:clicodetoolscpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerRcpprlangS7scalessimmertibbletidyselectutf8vctrsviridisLitewithr

Getting started with sandtablR
1. A cohort | 2. A scenario | 3. Simulate patient flow | 4. Decision paths | 5. Model the decisions | 6. Explain | The workbench | Provenance | Save and reproduce a run | Software environment
Rendered fromsandtablR.Rmdusingknitr::rmarkdown

Last update: 2026-10-28
Started: 2026-10-14

The model bench: open and closed boxes
Define the target before comparing models | The bench | Read the comparison | Explaining both the same way | Caveats | Software environment
Rendered frommodel-bench.Rmdusingknitr::rmarkdown

Last update: 2026-10-28
Started: 2026-10-14

Readme and manuals

Help Manual

Help pageTopics
Coerce a scenario to a tibbleas_tibble.scenario
Plot a scenarioautoplot.scenario
Format a patient cardformat.patient_card
Predict from a fitted mass-casualty modelpredict.sdt_model
Add participant decisions to a cohortsdt_add_decisions
The sandtablR workbench as a Shiny app objectsdt_app
Server for the sandtablR workbenchsdt_app_server
User interface for the sandtablR workbenchsdt_app_ui
Overwrite a cohort's placeholders with the gold standardsdt_apply_gold_standard
Display labels for board areassdt_area_labels
Explode a cohort into patient cardssdt_as_patient_cards
Build a validated casualty cohortsdt_cohort
Agreement between two labellings of the same casualtiessdt_consistency_score
Aggregate participant metadata to course compositionsdt_course_composition
Score decision consistencysdt_decision_consistency
Build decision paths from a game runsdt_decision_paths
Describe a table without hiding what is missingformat.sdt_describe print.sdt_describe sdt_describe
Describe a participant registersdt_describe_participants
The display-ready shape of a descriptive tablesdt_describe_render
Model engines available to the workbenchsdt_engines
Score how faithfully a simulation reproduces triage errorsdt_error_fidelity
Explain a fitted mass-casualty modelsdt_explain
Export a simulation run as a self-describing bundlesdt_export_simulation
Score how faithful a simulation is to the real thingsdt_fidelity
Fit a triage or therapy classification modelsdt_fit
Fit a hierarchical model of how teams behavesdt_fit_behaviour
Fit a model of triage error, with its between-team variancesdt_fit_triage_error
Permutation variable importancesdt_importance
The metric set the workbench scores onsdt_metric_set
Metrics for a fitted modelsdt_metrics
Normalisation dictionary for participant metadatasdt_participant_dictionary
Descriptives that state their denominatorsdt_participant_summary
Create a patient cardsdt_patient_card
Draw the board, with the casualties standing on itsdt_plot_board
Plot the end-of-game distribution against the published referencesdt_plot_end_state
Draw a fidelity tablesdt_plot_fidelity
Plot patient flow through the boardsdt_plot_flow
Plot decision-path sequencessdt_plot_sequences
Plot the triage mix of a scenariosdt_plot_triage_mix
Plot resource utilisation from a game runsdt_plot_utilisation
Held-out predictions from a fitted modelsdt_predictions
Dependence profiles for a fitted modelsdt_profile
Read the gold-standard triage codebooksdt_read_gold_standard
Read the TDSC course and group metadata registersdt_read_participants
Reference distributions for the mass-casualty domainsdt_reference
The horizon the engine is calibrated onsdt_reference_horizon
The scenario the engine is calibrated onsdt_reference_scenario
ROC curve for a fitted modelsdt_roc
Launch the sandtablR workbenchsdt_run_app
Turn a discrete-event game run into a (group, card) behaviour framesdt_run_behaviour
Build a mass-casualty scenariosdt_scenario
Cluster decision pathssdt_seq_cluster
Build a TraMineR state-sequence objectsdt_seqdef
Attribution for one casualtysdt_shap
Run a mass-casualty patient-flow simulationsdt_simulate
Simulate new groups from a fitted behaviour modelsdt_simulate_groups
Simulate triage calls from a fitted error modelsdt_simulate_triage
Score a synthetic replica against its seed cohortsdt_synthesis_utility
Synthesise a releasable replica of a real cohortsdt_synthesise
Generate a synthetic mass-casualty cohortsdt_synthetic_cohort
A tabular transformer specificationsdt_transformer
Score triage calls against the truthsdt_triage_accuracy
Controlled vocabularies for the mass-casualty domainsdt_board_areas sdt_diagnostics sdt_injury_regions sdt_life_range sdt_sex_levels sdt_therapy_levels sdt_triage_levels sdt_vocabularies
Screen every engine on one cohortsdt_workflowset
End-of-game location distributionsummary.game_run
Validate a casualty cohortvalidate_cohort
Validate a patient cardvalidate_patient_card