Adaptive Subgroup Selection in Sequential Trials

### get knitr just the way we like it

knitr::opts_chunk$set(
  message = FALSE,
  warning = FALSE,
  error = FALSE,
  tidy = FALSE,
  cache = FALSE
)

Introduction

ASSISTant is an R package for Adaptive Subgroup Selection In Sequential Trials. This vignette reproduces all the simulations in the original paper of Lai, Lavori and Liao [-@Lai2014191].

NOTE The number of simulations has been drastically reduced in this vignette in order to avoid taxing CRAN servers. The full_doc sources contain the complete sources and output; see files in the directory

system.file("full_doc", package="ASSISTant")
library(ASSISTant)
data(LLL.SETTINGS)
str(LLL.SETTINGS)

The LLL.SETTINGS list contains all the scenarios described in the paper.

Table 1 Results

Scenario S0

This is the null setting.

scenario <- LLL.SETTINGS$scenarios$S0
designParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
designA <- ASSISTDesign$new(trialParameters = LLL.SETTINGS$trialParameters,
                            designParameters = designParameters)
print(designA)
result <- designA$explore(numberOfSimulations = 50, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S1

scenario <- LLL.SETTINGS$scenarios$S1
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S2

scenario <- LLL.SETTINGS$scenarios$S2
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S3

scenario <- LLL.SETTINGS$scenarios$S3
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S4

scenario <- LLL.SETTINGS$scenarios$S4
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S5

scenario <- LLL.SETTINGS$scenarios$S5
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S6

scenario <- LLL.SETTINGS$scenarios$S6
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S7

scenario <- LLL.SETTINGS$scenarios$S7
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S8

scenario <- LLL.SETTINGS$scenarios$S8
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S9

scenario <- LLL.SETTINGS$scenarios$S9
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S10

scenario <- LLL.SETTINGS$scenarios$S10
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table1,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50,
                          trueParameters = trueParameters, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Table 2 Results

Scenario S0

scenario <- LLL.SETTINGS$scenarios$S0
designParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
designA <- ASSISTDesign$new(trialParameters = LLL.SETTINGS$trialParameters,
                            designParameters = designParameters)
print(designA)
result <- designA$explore(numberOfSimulations = 50, showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S1

scenario <- LLL.SETTINGS$scenarios$S1
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S2

scenario <- LLL.SETTINGS$scenarios$S2
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S3

scenario <- LLL.SETTINGS$scenarios$S3
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S4

scenario <- LLL.SETTINGS$scenarios$S4
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S5

scenario <- LLL.SETTINGS$scenarios$S5
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S6

scenario <- LLL.SETTINGS$scenarios$S6
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S7

scenario <- LLL.SETTINGS$scenarios$S7
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S8

scenario <- LLL.SETTINGS$scenarios$S8
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S9

scenario <- LLL.SETTINGS$scenarios$S9
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

Alternative Scenario S10

scenario <- LLL.SETTINGS$scenarios$S10
trueParameters <- list(prevalence = LLL.SETTINGS$prevalences$table2,
                       mean = scenario$mean,
                       sd = scenario$sd)
result <- designA$explore(numberOfSimulations = 50, trueParameters = trueParameters,
                          showProgress = FALSE)
analysis <- designA$analyze(result)
print(designA$summary(analysis))

References



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ASSISTant documentation built on Dec. 2, 2022, 5:12 p.m.