R/print.cfo.R

In CFO: CFO-Type Designs in Phase I/II Clinical Trials

#'
#' Generate descriptive summary for objects returned by other functions
#'
#' Generate descriptive summary for objects returned by other functions.
#'
#' @param x the object returned by other functions
#' @param ... ignored arguments
#'
#'
#' @details \code{print()} prints the objects returned by other functions.
#'
#' @return \code{print()} prints the objects returned by other functions.
#'
#' @author Jialu Fang, Ninghao Zhang, Wenliang Wang, and Guosheng Yin
#' 
#' @note In the example, we set \code{nsimu = 5} for testing time considerations. In reality, \code{nsimu} 
#'    is typically set to 5000 to ensure the accuracy of the results.
#'
#' @examples
#'
#' ## settings for 1dCFO
#' nsimu <- 5; ncohort <- 12; cohortsize <- 3; init.level <- 1
#' p.true <- c(0.02, 0.05, 0.20, 0.28, 0.34, 0.40, 0.44); target <- 0.2
#' assess.window <- 3; accrual.rate <- 2; tte.para <- 0.5; accrual.dist <- 'unif'
#' 
#' ## summarize the object returned by CFO.next()
#' decision <- CFO.next(target = 0.2, cys = c(0, 1, 0), cns = c(3, 6, 0), currdose = 3)
#' print(decision)
#' 
#' ## summarize the object returned by lateonset.next()
#' enter.times<- c(0, 0.266, 0.638, 1.54, 2.48, 3.14, 3.32, 4.01, 4.39, 5.38, 5.76,
#'                6.54, 6.66, 6.93, 7.32, 7.65, 8.14, 8.74)
#' dlt.times<- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0.995, 0, 0, 0, 0, 0, 0, 0, 2.58)
#' current.t<- 9.41; ndose = 7
#' doses<-c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 3, 3, 3, 4, 4, 4)
#' decision <- lateonset.next(design = 'f-aCFO', target, ndose, currdose = 4, assess.window,   
#'                enter.times, dlt.times, current.t, doses)
#' print(decision)
#' 
#' ## summarize the object returned by CFO.selectmtd()
#' selmtd <- CFO.selectmtd(target=0.2, npts=c(3,3,27,3,0,0,0), ntox=c(0,0,4,2,0,0,0))
#' print(selmtd)
#' 
#' ## summarize the object returned by CFO.simu()
#' aCFOtrial <- CFO.simu(design = 'aCFO', target, p.true, init.level, ncohort, cohortsize, seed = 1)
#' print(aCFOtrial)
#' 
#' 
#' \donttest{
#' # This test may take longer than 5 seconds to run
#' # It is provided for illustration purposes only
#' # Users can run this code directly
#' 
#' ## summarize the object returned by lateonset.simu()
#' faCFOtrial <- lateonset.simu (design = 'f-aCFO', target, p.true, init.level,  
#'                 ncohort, cohortsize, assess.window, tte.para, accrual.rate, accrual.dist, seed = 1)
#' print(faCFOtrial)
#' 
#' ## summarize the object returned by CFO.oc()
#' faCFOoc <- CFO.oc (nsimu, design = 'f-aCFO', target, p.true, init.level, ncohort, cohortsize,
#'                       assess.window, tte.para, accrual.rate, accrual.dist, seeds = 1:nsimu)
#' print(faCFOoc)
#' 
#' ## settings for 2dCFO
#' p.true <- matrix(c(0.05, 0.10, 0.15, 0.30, 0.45,
#' 0.10, 0.15, 0.30, 0.45, 0.55,
#' 0.15, 0.30, 0.45, 0.50, 0.60), 
#' nrow = 3, ncol = 5, byrow = TRUE)
#' 
#' cns <- matrix(c(3, 3, 0,
#'                 0, 6, 0,
#'                 0, 0, 0), 
#'               nrow = 3, ncol = 3, byrow = TRUE)
#' cys <- matrix(c(0, 1, 0,
#'                 0, 2, 0,
#'                 0, 0, 0), 
#'               nrow = 3, ncol = 3, byrow = TRUE)
#' currdose <- c(2,3); target <- 0.3; ncohort <- 12; cohortsize <- 3
#' 
#' ## summarize the object returned by CFO2d.next()
#' decision <- CFO2d.next(target, cys, cns, currdose = currdose, seed = 1)
#' print(decision)
#' 
#' ## summarize the object returned by CFO2d.selectmtd()
#' ntox <- matrix(c(0, 0, 2, 0, 0, 0, 2, 7, 0, 0, 0, 2, 0, 0, 0), nrow = 3, ncol = 5, byrow = TRUE)
#' npts <- matrix(c(3, 0, 12, 0, 0, 3, 12, 24, 0, 0, 3, 3, 0, 0, 0), nrow = 3, ncol = 5, byrow = TRUE)
#' selmtd <- CFO2d.selectmtd(target=0.3, npts=npts, ntox=ntox)
#' print(selmtd)
#' 
#' ## summarize the object returned by CFO2d.simu()
#' CFO2dtrial <- CFO2d.simu(target, p.true, init.level = c(1,1), ncohort, cohortsize, seed = 1)
#' print(CFO2dtrial)
#' 
#' ## summarize the object returned by CFO2d.oc()
#' CFO2doc <- CFO2d.oc(nsimu = 5, target, p.true, init.level = c(1,1), ncohort, cohortsize, 
#'                     seeds = 1:5)
#' print(CFO2doc)
#' 
#' ## summarize the object returned by CFOeff.next()
#' decision <- CFOeff.next(target=0.4,axs=c(3,1,7,11,26),ays=c(0,0,0,0,6),
#'               ans= c(6, 3, 12, 17, 36), currdose = 3, mineff = 0.3)
#' print(decision)
#' 
#' ## summarize the object returned by CFOeff.simu()
#' target <- 0.30; mineff <- 0.30
#' prior.para = list(alp.prior = target, bet.prior = 1 - target, 
#'                   alp.prior.eff = 0.5, bet.prior.eff = 0.5)
#' p.true=c(0.05, 0.07, 0.1, 0.12, 0.16)
#' pE.true=c(0.35, 0.45, 0.5, 0.55, 0.75)
#' result <- CFOeff.simu(target, p.true, pE.true, ncohort, init.level, cohortsize,
#'                        prior.para, mineff = mineff, seed = 1)
#' print(result)
#' 
#' ## summarize the object returned by CFOeff.oc()
#' nsimu = 10
#' result <- CFOeff.oc(target, p.true, pE.true, prior.para, 
#'           init.level,cohortsize, ncohort, nsimu, mineff = mineff, seeds = 1:nsimu)
#' print(result)
#' }
#'
#' @export

print.cfo<-function(x,...){
  print.default(x)
}