print.bcrm {bcrm} | R Documentation |
Print information regarding a trial conducted using the Bayesian continuous reassessment method
Description
Print method for a trial or series of trials conducted using a
bcrm
model.
Usage
## S3 method for class 'bcrm'
print(x, tox.cutpoints = NULL, trajectories = FALSE,
threep3 = FALSE, ...)
Arguments
x |
An object of class "bcrm" or "bcrm.sim" as returned by
|
tox.cutpoints |
An optional argument passed to |
trajectories |
Should the individual simulation dose and outcome trajectories be returned? Defaults to FALSE. |
threep3 |
Should operating characteristics of a standard 3+3 rule-based
design be displayed alongside those from the |
... |
Further arguments passed to or from other methods |
Details
If a single trial is conducted, then the print
function
currently produces summary information about the design used, the data
observed, current posterior estimates of toxicity, and the next recommended
dose level. If a simulation study is conducted, then the following
operating characteristics are printed:
- Experimentation proportion
Proportion of patients recruited to each dose, and to each true region of toxicity, across the simulated trials
- Recommendation proportion
Proportion of trials that recommend each of the dose levels as the final maximum tolerated dose (i.e. with toxicity "closest" to the target toxicity level), and the associated regions of true toxicity for the recommended MTDs
If trajectories = TRUE
then the dose level
administered and outcome observed are returned as matrices for every patient
(column) in every simulation (row). If threep3 = TRUE
then the
operating characteristics of the standard 3+3 design are displayed alongside
those of the bcrm
design (see threep3
for more
details).
Value
The following two components are returned from
print.bcrm.sim
:
exp |
A matrix with number of rows equal to the number of doses, and number of columns equal to the number of simulations. Gives the experimentation proportions for each dose within each simulation. |
rec |
A vector with length equal to the number of simulations, giving the recommended MTD for each simulation. |
Author(s)
Michael Sweeting mjs212@medschl.cam.ac.uk (University of Cambridge, UK)
References
Sweeting M., Mander A., Sabin T. bcrm: Bayesian Continual Reassessment Method Designs for Phase I Dose-Finding Trials. Journal of Statistical Software (2013) 54: 1–26. http://www.jstatsoft.org/article/view/v054i13