GBOP2 (version 0.1.4)

GBOP2_maxP_TE: PSOGO: Power maximizing design with efficacy and toxicity boundaries

Description

This function implements PSOGO to find a power maximizing design with efficacy and toxicity boundaries.

Value

A list on design parameters and operating characteristics

Arguments

design

fixed as "optimal", cannot be modified by user

pso_method

method for single PSO, choose from "default", "quantum" or "dexp"

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

totalPatients

number of total patients

Nmin_cohort1

maximum number of patients

Nmin_increase

minimum number of first 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_all

power: Futile and toxic

nSwarm

nSwarm in PSO

maxIter

maxIter in PSO

nParallel

number of PSO ensemble

seed

Random seed for reproducibility

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.

Examples

# \donttest{
# init_cluster(2)
# GBOP2_maxP_TE(
# design = "optimal",
# nlooks = 1,
# skip_efficacy = NULL,
# skip_toxicity = NULL,
# totalPatients = 50,
# Nmin_cohort1 = 10,
# Nmin_increase = 5,
# p01 = 0.15,  
# p02 = 0.16,  
# p03 = 0.024, 
# p11 = 0.4,  
# p12 = 0.08,  
# p13 = 0.032, 
# err_eff = 1,  
# err_tox = 1 , 
# err_all = 0.1,  
# power_all = 0.8,
# nParallel = 3,
# seed = 5321,
# pso_method = "default",
# nSwarm = 32,
# maxIter = 100)
# stop_cluster()  # Only if init_cluster() was used
#  
message("Run GBOP2_minSS_singleE() manually for real optimization.")
# }