An R6 class encapsulating Cumulative-Cohort Designs

An R6 class encapsulating Cumulative-Cohort Designs

Details

TODO: Explain the hierarchy of model classes, including connections with the executable specifications set forth in exec/prolog/ccd.pl.

References

  1. Ivanova A, Flournoy N, Chung Y. Cumulative cohort design for dose-finding. Journal of Statistical Planning and Inference. 2007;137(7):2316-2327. doi: 10.1016/j.jspi.2006.07.009

  2. Liu S, Yuan Y. Bayesian optimal interval designs for phase I clinical trials. J R Stat Soc C. 2015;64(3):507-523. doi: 10.1111/rssc.12089

Super class

precautionary::Cpe -> Ccd

Methods

Inherited methods


Method new()

Usage

Ccd$new(escalate, deescalate, eliminate, cohort_max, enroll_max)

Arguments

escalate

Escalation boundary

deescalate

Deescalation boundary

eliminate

Elimination boundary

cohort_max

Upper bound on dose-wise enrollment

enroll_max

Upper bound on total enrollment

Details

Create a new Ccd object.

Returns

A Ccd object.

Examples

# TODO


Method applied()

Usage

Ccd$applied(x, o, last_dose, max_dose, ...)

Arguments

x

A dose-wise vector of toxicity counts

o

A dose-wise vector of non-toxicity counts

last_dose

The most recently given dose, as required to implement cumulative-cohort-based escalation decisions.

max_dose

An upper limit on future dose levels

...

Unused by Ccd; included for superclass method compatibility

Details

Return dose recommendation for given tox/no-tox tallies.

Returns

An object with components:

  • $stop - logical value indicating whether stop is indicated

  • $mtd - integer value, the recommended dose

  • $max_dose - integer value, a dose not to be exceeded henceforth.


Method clone()

The objects of this class are cloneable with this method.

Usage

Ccd$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples


## ------------------------------------------------
## Method `Ccd$new`
## ------------------------------------------------

# TODO