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Select Experimental Treatments Using P-value Comparison

SelectExpWithPValueLessThanSpecified.Rd

At the interim analysis, experimental treatments are compared to the control using a chi-squared test. Treatments with p-values less than dMaxPValue are selected for stage 2. If no treatments meet the threshold, the treatment with the smallest p-value is selected. In the second stage, the randomization ratio will be 1:1 (experimental:control).

Usage

SelectExpWithPValueLessThanSpecified(
  SimData,
  DesignParam,
  LookInfo = NULL,
  UserParam = NULL
)

Arguments

SimData

Dataframe containing data generated in the current simulation.

DesignParam

List of design and simulation parameters required for treatment selection.

LookInfo

List containing design and simulation parameters that might be required for treatment selection.

UserParam

A list of user-defined parameters in East or East Horizon. Default is NULL. The list must contain the following named element:

UserParam$dMaxPValue

A value (0,1) specifying the chi-squared probability threshold for selecting treatments to advance. Treatments with p-values less than this threshold will advance to the second stage.

Value

A list containing:

TreatmentID

A vector of experimental treatment IDs selected to advance, e.g., 1, 2, ..., number of experimental treatments.

AllocRatio

A vector of allocation ratios for the selected treatments relative to control.

ErrorCode

An integer indicating success or error status:

ErrorCode = 0

No error.

ErrorCode > 0

Nonfatal error, current simulation aborted but subsequent simulations will run.

ErrorCode < 0

Fatal error, no further simulations attempted.

Note

  • The length of TreatmentID and AllocRatio must be the same.

  • The allocation ratio for control is always 1, and AllocRatio values are relative to this. For example, an allocation value of 2 means twice as many participants are randomized to the experimental treatment compared to control.

  • The order of AllocRatio should match TreatmentID, with corresponding elements assigned their respective allocation ratios.

  • The returned vector includes only TreatmentID values for experimental treatments. For example, TreatmentID = c(0, 1, 2) is invalid because control (0) should not be included.

  • At least one treatment and one allocation ratio must be returned.

Examples

# Example 1: Allocation in the second stage is 1:2:2 for Control:Experimental 1:Experimental 2
vSelectedTreatments <- c(1, 2)  # Experimental 1 and Experimental 2 both have an allocation ratio of 2.
vAllocationRatio    <- c(2, 2)
nErrorCode          <- 0
lReturn             <- list(TreatmentID = vSelectedTreatments, 
                             AllocRatio  = vAllocationRatio,
                             ErrorCode   = nErrorCode)
return(lReturn)
#> $TreatmentID
#> [1] 1 2
#> 
#> $AllocRatio
#> [1] 2 2
#> 
#> $ErrorCode
#> [1] 0
#> 

# Example 2: Allocation in the second stage is 1:1:2 for Control:Experimental 1:Experimental 2
vSelectedTreatments <- c(1, 2)  # Experimental 2 will receive twice as many patients as Experimental 1 or Control.
vAllocationRatio    <- c(1, 2)
nErrorCode          <- 0
lReturn             <- list(TreatmentID = vSelectedTreatments, 
                             AllocRatio  = vAllocationRatio,
                             ErrorCode   = nErrorCode)
return(lReturn)
#> $TreatmentID
#> [1] 1 2
#> 
#> $AllocRatio
#> [1] 1 2
#> 
#> $ErrorCode
#> [1] 0
#>