GBOP2_minSS_TE: PSOGO: Optimal/Minimax design with efficacy and toxicity...

In GBOP2: Generalized Bayesian Optimal Phase II Design (G-BOP2)

PSOGO: Optimal/Minimax design with efficacy and toxicity boundaries

Description

This function implements PSOGO to find an optimal or minimax design with efficacy and toxicity boundaries.

Usage

GBOP2_minSS_TE(
  design = "optimal",
  unified.u = 1,
  nlooks = 1,
  skip_efficacy = NULL,
  skip_toxicity = NULL,
  maxPatients = 5,
  Nmin_cohort1 = 1,
  Nmin_increase = 1,
  p01 = 0.3,
  p02 = 0.4,
  p03 = 0.2,
  p11 = 0.6,
  p12 = 0.2,
  p13 = 0.15,
  err_eff = 0.1,
  err_tox = 0.1,
  err_all = 0.05,
  power_eff = 0.8,
  power_tox = 0.8,
  power_all = 0.8,
  pso_method = "default",
  nParallel = NULL,
  seed = 5321,
  nSwarm = 1,
  maxIter = 1
)

Arguments

design	choose from "optimal", "minimax", or "unified"
unified.u	specify when design = "unified", u in zero to one
nlooks	number of interim looks
skip_efficacy	default is NULL, indicate skip efficacy as 1 and not skip as 0 in a vector
skip_toxicity	default is NULL, indicate skip toxicity as 1 and not skip as 0 in a vector
maxPatients	maximum number of patients
Nmin_cohort1	minimum number of first cohort
Nmin_increase	minimum number of increase in each cohort
p01	H0 for efficacy
p02	H0 for toxicity
p03	H0 for Eff and Tox
p11	H1 for efficacy
p12	H1 for toxicity
p13	H1 for Eff and Tox
err_eff	Type I error rate: Efficacious but toxic
err_tox	Type I error rate: Safe but futile
err_all	Type I error rate: Futile and toxic
power_eff	power: Efficacious but toxic
power_tox	power: Safe but futile
power_all	power: Futile and toxic
pso_method	"all" for using three distinct pso, otherwise indicate single pso method
nParallel	number of pso ensemble
seed	Random seed for reproducibility
nSwarm	nSwarm in PSO
maxIter	maxIter in PSO

Details

Parallel computing is only used when the user explicitly sets nCore > 1. No more than 2 cores should be used unless the user is aware and permits it. The function defaults to sequential execution. If multiple analyses are planned, consider using init_cluster(nCore) and stop_cluster() manually to control the backend.

Value

A list on design parameters and operating characteristics

Examples

# init_cluster(2)
#  GBOP2_minSS_TE(
#   design = "optimal", 
#    unified.u = 1, 
#    nlooks = 1, 
#    skip_efficacy = NULL, 
#    skip_toxicity = NULL, 
#    maxPatients = 25, 
#    Nmin_cohort1 = 10, 
#    Nmin_increase = 5, 
#    p01 = 0.3, 
#    p02 = 0.4, 
#    p03 = 0.2, 
#    p11 = 0.6, 
#    p12 = 0.2, 
#    p13 = 0.15, 
#    err_eff = 0.1, 
#    err_tox = 0.1, 
#    err_all = 0.05, 
#    power_eff = 0.8, 
#    power_tox = 0.8, 
#    power_all = 0.8, 
#    pso_method = "default", 
#    nParallel = 3, 
#    seed = 5321, 
#    nSwarm = 32, 
#    maxIter = 100
#  )
# stop_cluster()  # Only if init_cluster() was used
#  
message("Run GBOP2_minSS_singleE() manually for real optimization.")

GBOP2 documentation built on April 11, 2025, 5:42 p.m.