crmsim {dfcrm} | R Documentation |
crmsim
is used to generate simulation replicates of phase I
trial using the (group) CRM under a specified dose-toxicity
configuration.
crmsim(PI, prior, target, n, x0, nsim = 1, mcohort = 1, restrict = TRUE, count = TRUE, method = "bayes", model = "empiric", intcpt = 3, scale = sqrt(1.34), seed = 1009)
PI |
A vector of the true toxicity probabilites associated with the doses. |
prior |
A vector of initial guesses of toxicity probabilities
associated with the doses. Must be of same length as PI . |
target |
The target DLT rate. |
n |
Sample size of the trial. |
x0 |
The initial design. For one-stage TITE-CRM, it is a
single numeric value indicating the starting dose. For two-stage
TITE-CRM, it is a non-decreasing sequence of dose levels of length
n . |
nsim |
The number of simulations. Default is set at 1. |
mcohort |
The number of patients enrolled before the next model-based update. Default is set at 1, i.e., a fully sequential update. |
restrict |
If TRUE, restrictions apply during the trials to avoid (1) skipping doses in escalation and (2) escalation immediately after a toxic outcome (i.e., incoherent escalation). If FALSE, dose assignments are purely model-based. |
count |
If TRUE, the number of the current simulation replicate will be displayed. |
method |
A character string to specify the method for parameter estimation. The default method ``bayes'' estimates the model parameter by the posterior mean. Maximum likelihood estimation is specified by ``mle''. |
model |
A character string to specify the working model used in the method. The default model is ``empiric''. A one-parameter logistic model is specified by ``logistic''. |
intcpt |
The intercept of the working logistic model. The
default is 3. If model =``empiric'', this argument will be
ignored. |
scale |
Standard deviation of the normal prior of the model parameter. Default is sqrt(1.34). |
seed |
Seed of the random number generator. |
An object of class ``sim'' is returned, consisting of the operating
characteristics of the design specified. The time component of the
design is suppressed for the CRM simulator. All ``sim'' objects
generated by crmsim
contain at least the following components:
PI |
True toxicity rates. |
prior |
Initial guesses of toxicity rates. |
target |
The target probability of toxicity at the MTD. |
n |
Sample size. |
x0 |
The initial design. |
MTD |
Distribution of the MTD estimates. If nsim =1, this
is a single numeric value of the recommended MTD of in simulated
trial. |
level |
Average number of patients treated at the test doses. If
nsim =1, this is a vector of length n indicating the
doses assigned to the patients in the simulated trial. |
tox |
Average number of toxicities seen at the test doses. If
nsim =1, this is a vector of length n indicating the
toxicity outcomes of the patients in the simulated trial. |
beta.hat |
The estimates of the model parameter throughout the simulated trial(s). The dose assignment of the jth patient in each trial corresponds to the jth element in each row. |
final.est |
The final estimates of the model parameter of the simulated trials. |
O'Quigley, J. O., Pepe, M., and Fisher, L. (1990). Continual reassessment method: A practical design for phase I clinical trials in cancer. Biometrics 46:33-48.
Cheung, Y. K. (2005). Coherence principles in dose-finding studies. Biometrika 92:863-873.
PI <- c(0.10,0.20,0.40,0.50,0.60,0.65) prior <- c(0.05,0.10,0.20,0.35,0.50,0.70) target <- 0.2 x0 <- c(rep(1,3),rep(2,3),rep(3,3),rep(4,3),rep(5,3),rep(6,9)) # Generate a single replicate of two-stage group CRM trial of group size 3 foo <- crmsim(PI,prior,target,24,x0, mcohort=3) ## Not run: plot(foo,ask=T) # summarize trial graphically # Generate 10 replicates of CRM trial with 24 subjects foo10 <- crmsim(PI,prior,target,24,3,nsim=10,mcohort=2) foo10