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Integration Point: Analysis - Continuous Outcome with Repeated Measures

Gabriel Potvin

October 16, 2025

IntegrationPointAnalysisRepeatedMeasures.Rmd

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Input Variables

When creating a custom R script, you can optionally use specific variables provided by East Horizon’s engine itself. These variables are automatically available and do not need to be set by the user, except for the UserParam variable. Refer to the table below for the variables that are available for this integration point, outcome, and study objective.

Variable Type Description
SimData Data Frame Subject data generated in current simulation, one row per subject. To access these variables in your R code, use the syntax: SimData$NameOfTheVariable, replacing NameOfTheVariable with the appropriate variable name. See below for more information.
DesignParam List Input parameters which may be needed to compute test statistics and perform tests. To access these variables in your R code, use the syntax: DesignParam$NameOfTheVariable, replacing NameOfTheVariable with the appropriate variable name. See below for more information.
LookInfo List Input parameters related to multiple looks. Empty when Statistical Design = Fixed Sample, but still mandatory in the functions CyneRgy::GetDecisionString and CyneRgy::GetDecision. See below for more information.
AdaptInfo List Input parameters related to sample size re-estimation. See below for more information. Only applicable when Statistical Design = Group Sequential with Sample Size Re-Estimation.
UserParam List Contains all user-defined parameters specified in the East Horizon interface (refer to the Instructions section). To access these parameters in your R code, use the syntax: UserParam$NameOfTheVariable, replacing NameOfTheVariable with the appropriate parameter name.

Variables of SimData

Click here to explore the variables of SimData.

Variables of DesignParam

Click here to explore the variables of DesignParam.

Variables of LookInfo

Click here to explore the variables of LookInfo.

Expected Output Variable

East Horizon expects an output of a specific type. Refer to the table below for the expected output for this integration point:

Type Description
List A named list containing ErrorCode and one or multiple of the following members: Decision, AnalysisTime, TestStat, PrimDelta, SecDelta. See below for more information.

The output list can take different forms.

For Study Objective = Two Arm Confirmatory

Option 1 (Decision): Expected Members of the Output List

Members Type Description
Decision Integer Boundary crossing decision:
– 0: No boundary crossed.
– 1: Lower efficacy boundary crossed.
– 2: Upper efficacy boundary crossed.
– 3: Futility boundary crossed (only applicable when Statistical Design = Group Sequential).
– 4: Equivalence boundary crossed (not available in East Horizon Explore).
You can use the functions CyneRgy::GetDecisionString and CyneRgy::GetDecision to get the decision value. See the template below for the correct usage.
AnalysisTime Numeric Optional. Estimate of analysis time. For interim analyses, equivalent to look time; for final analysis, equivalent to study duration.
ErrorCode Integer Optional. Can be used to handle errors in your script:
– 0: No error.
– Positive Integer: Nonfatal error, the current simulation will be aborted, but the next simulation will proceed.
– Negative Integer: Fatal error, no further simulations will be attempted.

Note for Statistical Design = Group Sequential: When there is no efficacy boundary to be crossed, the return code of 0 stands for futility in the final look. Similarly, when there is no futility boundary to be crossed, the return code of 0 stands for efficacy in the final look. Use the functions CyneRgy::GetDecisionString and CyneRgy::GetDecision to get decision values in a simple way.

Option 2 (TestStat): Expected Members of the Output List

Members Type Description
TestStat Numeric Value of appropriate test statistic on Wald ﴾Z﴿ scale.
PrimDelta Numeric Estimate of primary contrast Delta. Required if LookInfo$FutBdryScale = 2 (futility boundary scale is Delta) and LookInfo$FutContrast = 0 (primary contrast). Only applicable when Statistical Design = Group Sequential.
SecDelta Numeric Estimate of secondary contrast Delta. Required if LookInfo$FutBdryScale = 2 (futility boundary scale is Delta) and LookInfo$FutContrast = 1 (secondary contrast). Only applicable when Statistical Design = Group Sequential.
AnalysisTime Numeric Optional. Estimate of analysis time. For interim analyses, equivalent to look time; for final analysis, equivalent to study duration.
ErrorCode Integer Optional. Can be used to handle errors in your script:
– 0: No error.
– Positive Integer: Nonfatal error, the current simulation will be aborted, but the next simulation will proceed.
– Negative Integer: Fatal error, no further simulations will be attempted.

Note for Statistical Design = Fixed Sample: As the design does not have any futility boundary, TestStat will be used to check for efficacy.

Notes for Statistical Design = Group Sequential:

  • If the design does not have any futility boundary, TestStat will be used to check for efficacy.
  • If LookInfo$FutBdryScale = 2 (futility boundary scale is Delta scale) and LookInfo$FutContrast = 0 (primary contrast), TestStat will be used to check for efficacy and PrimDelta will be used to check for futility.
  • If LookInfo$FutBdryScale = 2 (futility boundary scale is Delta scale) and LookInfo$FutContrast = 1 (secondary contrast), TestStat will be used to check for efficacy and SecDelta will be used to check for futility.

Minimal Templates

Your R script could contain a function such as these ones, with a name of your choice. All input variables must be declared, even if they are not used in the script. We recommend always declaring UserParam as a default NULL value in the function arguments, as this will ensure that the same function will work regardless of whether the user has specified any custom parameters in East Horizon. A detailed template with step-by-step explanations is available here: Analyze.RepeatedMeasures.R.

For Study Objective = Two Arm Confirmatory

Minimal Template for Option 1 (Decision)

For Statistical Design = Fixed Sample 
PerformDecision <- function( SimData, DesignParam, LookInfo = NULL, UserParam = NULL )
{
    library( CyneRgy )
    nError              <- 0 # Error handling (no error)
    
    # This is an example using GetDecisionString and GetDecision.
    
    # Write the actual code here.
    # It is a fixed sample design, so no interim look nor futility check.
    bFAEfficacyCheck <- TRUE # If TRUE, declares efficacy.
    # Usually, bFAEfficacyCheck would be a conditional statement such as 'dTValue > dBoundary'.
    
    # These variables are set because it is a fixed sample design.
    nQtyOfLooks          <- 1
    nLookIndex           <- 1
    nQtyOfPatsInAnalysis <- nrow( SimData )
    TailType             <- DesignParam$TailType
    
    strDecision <- CyneRgy::GetDecisionString( LookInfo, nLookIndex, nQtyOfLooks,
                                               bFAEfficacyCondition = bFAEfficacyCheck)

    nDecision <- CyneRgy::GetDecision( strDecision, DesignParam, LookInfo )
    
    return( list( Decision = as.integer( nDecision ), ErrorCode = as.integer( nError ) ) )
}
For Statistical Design = Group Sequential 
PerformDecision <- function( SimData, DesignParam, LookInfo = NULL, UserParam = NULL )
{
    library( CyneRgy )
    nError              <- 0 # Error handling (no error)
    
    # This is an example using GetDecisionString and GetDecision.
    
    # Write the actual code here.
    # It is a group sequential design, so interim looks and futility check are possible.
    bIAEfficacyCheck <- TRUE # If TRUE, declares efficacy at the interim look.
    bIAFutilityCheck <- FALSE # If TRUE, declares futility at the interim look.
    bFAEfficacyCheck <- TRUE # If TRUE, declares efficacy at the final look.
    # Usually, the Check variables would be conditional statements such as 'dTValue > dBoundary'.
    
    # These variables are from LookInfo because it is a group sequential design.
    nQtyOfLooks          <- LookInfo$NumLooks
    nLookIndex           <- LookInfo$CurrLookIndex
    nQtyOfPatsInAnalysis <- LookInfo$CumCompleters[ nLookIndex ]
    RejType              <- LookInfo$RejType
    TailType             <- DesignParam$TailType
    
    strDecision <- CyneRgy::GetDecisionString( LookInfo, nLookIndex, nQtyOfLooks,
                                               bIAEfficacyCondition = bIAEfficacyCheck,
                                               bIAFutilityCondition = bIAFutilityCheck,
                                               bFAEfficacyCondition = bFAEfficacyCheck )

    nDecision <- CyneRgy::GetDecision( strDecision, DesignParam, LookInfo )
    
    return( list ( Decision = as.integer( nDecision ), ErrorCode = as.integer( nError ) ) )
}

Minimal Template for Option 2 (TestStat)

For Statistical Design = Fixed Sample 
ComputeTestStat <- function( SimData, DesignParam, LookInfo = NULL, UserParam = NULL )
{
    nError              <- 0 # Error handling (no error)
    dTestStatistic      <- 0
    
    # Write the actual code here.
    # Store the computed test statistic in dTestStatistic.
    
    return( list( TestStat = as.double( dTestStatistic ), ErrorCode = as.integer( nError ) ) )
}
For Statistical Design = Group Sequential 
ComputeTestStat <- function( SimData, DesignParam, LookInfo = NULL, UserParam = NULL )
{
    nError              <- 0 # Error handling (no error)
    dTestStatistic      <- 0
    dPrimeDelta         <- 0 # Use if futility boundary scale is Delta and primary contrast
    dSecDelta           <- 0 # Use if futility boundary scale is Delta and secondary contrast
    
    
    # Write the actual code here.
    # Store the computed test statistic in dTestStatistic.
    # Compute dDelta, dCtrlCompleters, dTrmtCompleters, dCtrlPi if needed.
    
    return( list( TestStat = as.double( dTestStatistic ),
                  PrimeDelta = as.double( dPrimeDelta ), # Include if futility boundary scale is Delta and primary contrast
                  SecDelta = as.double( dSecDelta ), # Include if futility boundary scale is Delta and secondary contrast
                  ErrorCode = as.integer( nError ) ) )
}

Example

Explore the following example for more context:

  1. Analyze.RepeatedMeasures.R