OC.rule.bin {stoppingrule}

Operating Characteristics Function (Binary Data)

Description

Compute operating characteristics for a stopping rule at a set of toxicity rates. Characteristics calculated include the overall rejection probability, the expected number of patients evaluated, and the expected number of events.

Usage

OC.rule.bin(rule, ps, tau = NULL, A = NULL)

Arguments

rule

A rule.bin object calculated by calc.rule.bin() function

ps

A vector of toxicity probabilities at which the operating characteristics will be computed

tau

Length of observation period

A

Length of the enrollment period.

Details

If tau and A are specified, the expected number of events includes events among patients who are still pending evaluation at the time of early stopping, computed under an assumption of a random uniform accrual distribution. Otherwise, only events that occurred prior to stopping are included, as the number of events occurring in pending patients depends on tau and A.

Value

A matrix with columns containing the toxicity probabilities ps, the corresponding rejection probabilities, and the corresponding expected number of events. If tau and A are also specified, the expected numbers of enrolled patients and the expected calendar time at the point of stopping/study end are also included.

Examples

# Binomial Pocock test in 50 patient cohort at 10% level, expected toxicity probability of 20%
poc_rule = calc.rule.bin(ns=1:50,p0=0.20,alpha=0.10,type="Pocock")

# Bayesian beta-binomial method of Geller et al. in 50 patient cohort at 10% level,
# expected toxicity probability of 20%
bb_rule = calc.rule.bin(ns=1:50,p0=0.20,alpha=0.10,type="BB",param=c(2,8))

# Compute operating characteristics at toxicity probabilities of 20%, 25%, 30%, 35%, and 40%
OC.rule.bin(rule=poc_rule,ps=seq(0.2,0.4,0.05))
OC.rule.bin(rule=bb_rule,ps=seq(0.2,0.4,0.05),tau=30,A=730)