Skip to contents

Analyze Binary Data Using Proportion Limits of Confidence Interval

AnalyzeBinaryUsingPropLimitsOfCI.Rd

This function analyzes binary data using a simplified confidence interval (CI) limits design. It determines whether to make a "Go" or "No Go" decision based on the treatment difference and user-specified thresholds for the CI lower and upper limits. The analysis uses the prop.test function from base R to compute CIs at a user-defined confidence level.

The decision logic is as follows:

  • If the lower limit (LL) of the CI is greater than UserParam$dLowerLimit, a "Go" decision is made.

  • If a "Go" decision is not made, and the upper limit (UL) of the CI is less than UserParam$dUpperLimit, a "No Go" decision is made.

  • Otherwise, continue to the next analysis.

  • At the final analysis:

    • If LL > UserParam$dLowerLimit, a "Go" decision is made.

    • Otherwise, a "No Go" decision is made.

Usage

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

Arguments

SimData

A data frame containing the data generated in the current simulation.

DesignParam

A list of design and simulation parameters required for the analysis.

LookInfo

A list containing input parameters related to multiple looks, which are used to compute test statistics and perform tests. Important variables include:

  • LookInfo$NumLooks: Integer, number of looks in the study.

  • LookInfo$CurrLookIndex: Integer, current look index (starting from 1).

  • LookInfo$CumEvents: Vector, cumulative number of events at each look.

  • LookInfo$RejType: Code representing rejection types. Possible values include:

  • Efficacy Only:

    • 0: 1-Sided Efficacy Upper.

    • 2: 1-Sided Efficacy Lower.

  • Futility Only:

    • 1: 1-Sided Futility Upper.

    • 3: 1-Sided Futility Lower.

  • Efficacy and Futility:

    • 4: 1-Sided Efficacy Upper and Futility Lower.

    • 5: 1-Sided Efficacy Lower and Futility Upper.

UserParam

A list of user-defined parameters with the following required elements:

dLowerLimit

A value (0,1) specifying the lower limit, e.g., Minimum Acceptable Value (MAV).

dUpperLimit

A value (0,1) specifying the upper limit for the confidence interval, e.g., Target Value (TV).

dConfLevel

A value (0,1) specifying the confidence level for the prop.test function.

Value

A list containing the following elements:

TestStat

A double representing the computed test statistic.

Decision

Required integer value indicating the decision made:

0

No boundary crossed (neither efficacy nor futility).

1

Lower efficacy boundary crossed.

2

Upper efficacy boundary crossed.

3

Futility boundary crossed.

4

Equivalence boundary crossed.

ErrorCode

Optional integer value:

0

No error.

> 0

Non-fatal error; current simulation is aborted but subsequent simulations continue.

< 0

Fatal error; no further simulations are attempted.

Delta

Estimated difference between experimental and control treatments.

Note

In this example, the boundary information computed and sent from East or East Horizon is ignored to implement this decision approach.