RuleDesignOrdinal-class: 'RuleDesignOrdinal'

In crmPack: Object-Oriented Implementation of Dose Escalation Designs

RuleDesignOrdinal

Description

RuleDesignOrdinal is the class for rule-based designs. The difference between this class and the DesignOrdinal class is that RuleDesignOrdinal does not contain model, stopping and increments slots.

Usage

RuleDesignOrdinal(next_best, cohort_size, data, starting_dose)

.DefaultRuleDesignOrdinal()

Arguments

next_best	(NextBestOrdinal) see slot definition.
cohort_size	(CohortSize) see slot definition.
data	(DataOrdinal) see slot definition.
starting_dose	(number) see slot definition.

Details

Please note that the cohort size rules need to be wrapped into the corresponding CohortSizeOrdinal class, before a successful evaluation of the corresponding methods can take place. Note also that these wrappers cannot be nested, i.e., you cannot have a CohortSizeOrdinal inside another CohortSizeOrdinal (which also would not make sense) because it would not be clear which event grade to use for the methods calculation. However, multiple rules can be combined using the operators defined, e.g., CohortSizeMin(list(CohortSizeOrdinal(1L, rule1), CohortSizeOrdinal(2L, rule2))).

Slots

next_best

(NextBestOrdinal)
how to find the next best dose.

cohort_size

(CohortSize)
rules for the cohort sizes.

data

(DataOrdinal)
specifies dose grid, any previous data, etc.

starting_dose

(number)
the starting dose, it must lie on the dose grid in data.

Note

Typically, end users will not use the .DefaultRuleDesignOrdinal() function.

Examples

RuleDesignOrdinal(
  next_best = NextBestOrdinal(
    1L,
    NextBestMTD(
      target = 0.25,
      derive = function(x) median(x, na.rm = TRUE)
    )
  ),
  cohort_size = CohortSizeOrdinal(1L, CohortSizeConst(size = 3L)),
  data = DataOrdinal(doseGrid = c(5, 10, 15, 25, 35, 50, 80)),
  starting_dose = 5
)

crmPack documentation built on Nov. 29, 2025, 5:07 p.m.