Function reference • escalation

All functions
`CorrelatedPatientSample`	A sample of patients that experience correlated events in simulations.
`PatientSample`	A sample of patients to use in simulations.
`as_tibble(<dose_paths>)`	Cast `dose_paths` object to `tibble`.
`as_tibble(<selector>)`	Cast `dose_selector` object to `tibble`.
`as_tibble(<simulations_collection>)`	Convert a simulations_collection to a tibble
`calculate_probabilities()`	Calculate dose-path probabilities
`check_dose_selector_consistency()`	Check the consistency of a dose_selector instance
`cohort()`	Cohort numbers of evaluated patients.
`cohorts_of_n()`	Sample times between patient arrivals using the exponential distribution.
`continue()`	Should this dose-finding experiment continue?
`convergence_plot()`	Plot the convergence processes from a collection of simulations.
`crystallised_dose_paths()`	Dose-paths with probabilities attached.
`demand_n_at_dose()`	Demand there are n patients at a dose before condisdering stopping.
`dont_skip_doses()`	Prevent skipping of doses.
`dose_admissible()`	Is each dose admissible?
`dose_indices()`	Dose indices
`dose_paths()`	Dose pathways
`dose_paths_function()`	Get function for calculating dose pathways.
`doses_given()`	Doses given to patients.
`eff()`	Binary efficacy outcomes.
`eff_at_dose()`	Number of toxicities seen at each dose.
`eff_limit()`	Efficacy rate limit
`empiric_eff_rate()`	Observed efficacy rate at each dose.
`empiric_tox_rate()`	Observed toxicity rate at each dose.
`enforce_three_plus_three()`	Enforce that a trial path has followed the 3+3 method.
`escalation-package` `escalation`	The 'escalation' package.
`fit()`	Fit a dose-finding model.
`follow_path()`	Follow a pre-determined dose administration path.
`get_boin()`	Get an object to fit the BOIN model using the BOIN package.
`get_boin12()`	Get an object to fit the BOIN12 model for phase I/II dose-finding.
`get_dfcrm()`	Get an object to fit the CRM model using the dfcrm package.
`get_dfcrm_tite()`	Get an object to fit the TITE-CRM model using the dfcrm package.
`get_dose_paths()`	Calculate future dose paths.
`get_empiric_crm_skeleton_weights()`	Get posterior model weights for several empiric CRM skeletons.
`get_mtpi()`	Get an object to fit the mTPI dose-finding model.
`get_mtpi2()`	Get an object to fit the mTPI-2 dose-finding model.
`get_potential_outcomes()`	Get potential outcomes from a list of PatientSamples
`get_random_selector()`	Get an object to fit a dose-selector that randomly selects doses.
`get_three_plus_three()`	Get an object to fit the 3+3 model.
`get_tpi()`	Get an object to fit the TPI dose-finding model.
`get_trialr_crm()`	Get an object to fit the CRM model using the trialr package.
`get_trialr_crm_tite()`	Get an object to fit the TITE-CRM model using the trialr package.
`get_trialr_efftox()`	Get an object to fit the EffTox model using the trialr package.
`get_trialr_nbg()`	Get an object to fit the NBG dose-finding model using the trialr package.
`get_trialr_nbg_tite()`	Get an object to fit a TITE version of the NBG dose-finding model using trialr
`get_wages_and_tait()`	Get an object to fit Wages & Tait's model for phase I/II dose-finding.
`graph_paths()`	Visualise dose-paths as a graph
`is_randomising()`	Is this selector currently randomly allocating doses?
`linear_follow_up_weight()`	Weights for tolerance and toxicity events using linear function of time
`mean_prob_eff()`	Mean efficacy rate at each dose.
`mean_prob_tox()`	Mean toxicity rate at each dose.
`median_prob_eff()`	Median efficacy rate at each dose.
`median_prob_tox()`	Median toxicity rate at each dose.
`model_frame()`	Model data-frame.
`n_at_dose()`	Number of patients treated at each dose.
`n_at_recommended_dose()`	Number of patients treated at the recommended dose.
`num_cohort_outcomes()`	Number of different possible outcomes for a cohort of patients
`num_dose_path_nodes()`	Number of nodes in dose-paths analysis
`num_doses()`	Number of doses.
`num_eff()`	Total number of efficacies seen.
`num_patients()`	Number of patients evaluated.
`num_tox()`	Total number of toxicities seen.
`parse_phase1_2_outcomes()`	Parse a string of phase I/II dose-finding outcomes to vector notation.
`parse_phase1_outcomes()`	Parse a string of phase I dose-finding outcomes to vector notation.
`phase1_2_outcomes_to_cohorts()`	Break a phase I/II outcome string into a list of cohort parts.
`phase1_outcomes_to_cohorts()`	Break a phase I outcome string into a list of cohort parts.
`prob_administer()`	Percentage of patients treated at each dose.
`prob_eff_quantile()`	Quantile of the efficacy rate at each dose.
`prob_recommend()`	Probability of recommendation
`prob_tox_exceeds()` `prob_eff_exceeds()`	Probability that the toxicity rate exceeds some threshold.
`prob_tox_quantile()`	Quantile of the toxicity rate at each dose.
`prob_tox_samples()` `prob_eff_samples()`	Get samples of the probability of toxicity.
`recommended_dose()`	Recommended dose for next patient or cohort.
`select_boin12_obd()`	Select dose by BOIN12's OBD-choosing algorithm.
`select_boin_mtd()`	Select dose by BOIN's MTD-choosing algorithm.
`select_dose_by_cibp()`	Select dose by the CIBP selection criterion.
`select_mtpi2_mtd()`	Select dose by mTPI2's MTD-choosing algorithm.
`select_mtpi_mtd()`	Select dose by mTPI's MTD-choosing algorithm.
`select_tpi_mtd()`	Select dose by TPI's MTD-choosing algorithm.
`selector()`	Dose selector.
`selector_factory()`	Dose selector factory.
`simulate_compare()`	Simulate clinical trials for several designs using common patients.
`simulate_trials()`	Simulate clinical trials.
`simulation_function()`	Get function for simulating trials.
`simulations()`	Simulated trials.
`simulations_collection()`	Make an instance of type `simulations_collection`
`spread_paths()`	Spread the information in dose_finding_paths object to a wide data.frame format.
`stack_sims_vert()`	Stack `simulations_collection` results vertically
`stop_at_n()`	Stop when there are n patients in total.
`stop_when_n_at_dose()`	Stop when there are n patients at a dose.
`stop_when_too_toxic()`	Stop trial and recommend no dose when a dose is too toxic.
`stop_when_tox_ci_covered()`	Stop when uncertainty interval of prob tox is covered.
`supports_sampling()`	Does this selector support sampling of outcomes?
`three_plus_three()`	Fit the 3+3 model to some outcomes.
`tox()`	Binary toxicity outcomes.
`tox_at_dose()`	Number of toxicities seen at each dose.
`tox_limit()`	Toxicity rate limit
`tox_target()`	Target toxicity rate
`trial_duration()`	Duration of trials.
`try_rescue_dose()`	Demand that a rescue dose is tried before stopping is permitted.
`utility()`	Utility score of each dose.
`weight()`	Outcome weights.

Reference

All functions