| titecrm {titecrm} | R Documentation |
Returns an object of class mtd that summarizes the dose
assignments and recommends a dose for the next patient
in a phase I trial using TITE-CRM.
titecrm(prior, target, tox, level, n=length(level), weights=NULL, followup=NULL, obswin=NULL, scheme="linear", dosename=NULL, include=1:n, pid=1:n, method="bayes", scale=sqrt(1.34), model.detail=TRUE, patient.detail=TRUE)
prior |
A vector of initial estimates of toxicity probabilities associated the doses. |
target |
The target DLT rate. |
tox |
A vector of patient outcomes; 1 indicates a toxicity, 0 otherwise. |
level |
A vector of dose levels assigned to patients. The length
of level must be equal to that of tox. |
weights |
A vector of weights assigned to observations. A
weight must be between 0 and 1. If given, the arguments
followup, obswin, and scheme will be ignored.
If not supplied, users must provide followup and
obswin. The length of weights must be equal to that
of tox. |
n |
The number of enrollments. |
followup |
A vector of follow-up times of patients. If not
supplied, users must provide weights. |
obswin |
The observation window with respect to which the MTD is
defined. If not supplied, users must provide weights. |
scheme |
A character string to specify the method for assigning weights. Default is ``linear''. Adaptive weight using Kaplan-Meier ``KM'' is to be made available. |
dosename |
A vector containing the names of the regimens/doses
used. The length of dosename must be equal to that of
prior. |
include |
A subset of patients included in the dose calculation. |
pid |
Patient ID provided in the study. Its length must be equal
to that of level. |
method |
A character string to specify the method for parameter estimation. The default method ``bayes'' estimates the model parameter by the posterior mean. Estimation using ``mle'' is to be made available. |
scale |
Standard deviation of the normal prior of the model parameter. Default is sqrt(1.34). |
model.detail |
If TRUE, the model content of an ``mtd'' object will be displayed in detail. |
patient.detail |
If TRUE, patient summary will be given in detail. |
Dose-toxicity relationship is assumed as an empiric power model $a_i^{exp(β)}$ where $a_i$ is the initial estimate of toxicity probability of dose level i and the model parameter $β$ has a normal prior with mean 0 and scale to be provided by users.
An object of class ``mtd'' is returned, consisting of the summary of dose assignments thus far and the recommendation of dose for the next patient.
prior |
Initial estimates of toxicity probabilities. |
ptox |
Updated estimates of toxicity probabilities. |
target |
The target probability of toxicity at the MTD. |
recommend |
The recommended dose level for the next patient. |
scale |
The standard deviation of the normal prior. |
estimate |
Estimate of the model parameter. |
level |
Dose levels assigned to patients. |
tox |
Patients' toxicity indications. |
followup |
Follow-up times of patients. |
obswin |
Observation window with respect to which the MTD is defined. |
weights |
Weights assigned to patients. |
scheme |
Weighting scheme. |
Cheung, Y. K. and Chappell, R. (2000). Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 56:1177-1182.
# Create a simple data set prior <- c(0.05,0.10,0.20,0.35,0.50,0.70) target <- 0.2 level <- c(3,4,4,3,3,4,3,2,2,2) y <- c(0,0,1,0,0,1,1,0,0,0) u <- c(1,1,0.8,1,1,0.6,0.45,0.25,1/6,1/12) tau <- 1 foo <- titecrm(prior,target,y,level,followup=u,obswin=1) rec <- foo$recommend # recommend a dose level for next patient