RPWRule: Randomized Play-the-winner Rule

In grouprar: Group Response Adaptive Randomization for Clinical Trials

Randomized Play-the-winner Rule

Description

Simulating the randomized play-the-winner rule (two arms) with two-sided hypothesis testing in a clinical trial context.

Usage

RPWRule(k, p, ssn, Y0 = NULL, nsim = 2000, alpha = 0.05, test.fun = NULL,
        typeI = FALSE, seed = NULL)

Arguments

k	A positive integer. The number of treatment groups in the trial. Only k = 2 is supported, and other values give an error; see WeiUrn for more than two arms.
p	A vector of length k with values between 0 and 1. The true success rates of the treatments, used to generate data for the simulations.
ssn	A positive integer. The total number of participants in each simulated trial.
Y0	A vector of length k giving the initial urn composition (number of balls of each treatment type). For instance, if Y0 = c(1, 1), the first patient is assigned to each treatment with probability Y0 / sum(Y0). If Y0 is NULL (default), it is set to a vector of k ones.
nsim	A positive integer. The number of simulated trials, with a default value of 2000.
alpha	A number between 0 and 1. The significance level of the two-sided test, with a default value of 0.05.
test.fun	An optional function function(outcome, assignment) that returns the p-value of a test for one simulated trial, where outcome holds the observed responses and assignment the treatment labels (integers 1 to k); missing responses are removed first. The null hypothesis is rejected when the p-value is at most alpha. The default NULL uses the built-in two-sided tests: the t-test for two arms and the Wald chi-squared test of equal means for more than two arms (for binary responses, if some arms have no variability, the variances are computed from (S_k + 1)/(n_k + 2) as in Agresti and Caffo, 2000).
typeI	Logical. If TRUE, the simulation is repeated under the null hypothesis, with every arm's success rate set to the average of p, and the rejection rate is reported as type I error. The default is FALSE.
seed	An optional integer passed to set.seed before simulating, so that the results can be reproduced. The default NULL leaves the random number generator unchanged.

Details

The randomized play-the-winner rule allocates future subjects in a clinical trial to treatment groups based on the performance of previously treated subjects. A ball is drawn from the urn to assign the next subject. A success on a treatment adds a ball of the same type to the urn, and a failure adds a ball of the other type. This increases the chance that future patients are assigned to the better-performing treatment.

Value

An object of class "grouprar", a list that is printed as a short summary (see print.grouprar), with the following elements.

method	The name of the procedure.
sample size	The total sample size.
parameter	The true success rates used in the simulations, named pA, pB, ...
propotion	The mean allocation proportion of each arm over the simulations, named treatment A, treatment B, ...
sd of propotion	The standard deviation of the allocation proportion of each arm over the simulations.
failure rate	The mean failure rate over the simulations.
sd of failure rate	The standard deviation of the failure rate (or mean response) over the simulations.
power	The proportion of simulated trials that reject the null hypothesis of equal success rates. Simulations in which the test cannot be computed are dropped.
data: failureRate	The failure rate (or mean response) of each simulated trial.
data: test	The test decision of each simulated trial (1 = reject).
data: assignment	The treatment assignments of the last simulated trial.
data: propotion	A data frame with the allocation proportions of each simulated trial.
data: allocation	An nsim by ssn matrix with the treatment assignments of every simulated trial.
type I error	Only if typeI = TRUE. The rejection rate under the null hypothesis.

References

Wei, L. J. and Durham, S. (1978). The randomized play-the-winner rule in medical trials. Journal of the American Statistical Association, 73(364), 840-843. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01621459.1978.10480109")}

Examples

## a simple use
RPW.res <- RPWRule(k = 2, p = c(0.7, 0.8), ssn = 200, Y0 = NULL, nsim = 100, alpha = 0.05)
## view the output
RPW.res


  ## view all simulation settings
  RPW.res[["method"]]
  RPW.res[["parameter"]]

  ## view the simulation results
  RPW.res[["propotion"]]
  RPW.res[["failure rate"]]
  RPW.res[["power"]]
  RPW.res[["data: assignment"]]
  

grouprar documentation built on Oct. 9, 2026, 9:07 a.m.