integrateExpectedInformation: Integrate over information

In optconerrf: Optimal Monotone Conditional Error Functions

Integrate over information

Description

Internal function used by getExpectedSecondStageInformation() to calculate the integral over the information.

Usage

integrateExpectedInformation(
  firstStagePValue,
  design,
  likelihoodRatioDistribution,
  ...
)

Arguments

firstStagePValue	First-stage p-value or p-values. Must be a numeric vector between 0 and 1.
design	An object of class TrialDesignOptimalConditionalError created by getDesignOptimalConditionalErrorFunction(). Contains all necessary arguments to calculate the optimal conditional error function for the specified case.
likelihoodRatioDistribution	The distribution to be used for the effect size of the likelihood ratio in the optimal conditional error function. Options are "fixed", "normal", "exp", "unif", "maxlr" for fixed effect size, normally distributed, exponentially distributed, uniformly distributed prior of the effect size and maximum likelihood ratio, respectively. Each case requires different additional specifications: likelihoodRatioDistribution="fixed" uses one (or more) fixed effect sizes for the likelihood ratio and requires the parameter deltaLR which provides the mean difference under which to calculate the likelihood ratio. If deltaLR contains multiple values, they may be weighted using an additional argument weightsDeltaLR. Omitting weightsDeltaLR automatically leads to equal weighting. likelihoodRatioDistribution="normal" uses a normal prior for the effect size and requires parameters deltaLR and tauLR for the mean and standard deviation of the normal distribution (both on mean difference scale). likelihoodRatioDistribution="exp" uses an exponential prior for the effect size and requires the parameter kappaLR which is the mean of the exponential distribution (on the mean difference scale). likelihoodRatioDistribution="unif" uses a uniform prior for the effect size and requires the specification of deltaMaxLR, which is the maximum of the support for the uniform likelihood ratio distribution (on the mean difference scale). likelihoodRatioDistribution="maxlr" estimates the non-centrality parameter to be used for the likelihood ratio from the data. No additional parameters must be specified.
...	Additional arguments needed for getOptimalConditionalError() and getLikelihoodRatio().

Value

Integral over the information of the second stage

optconerrf documentation built on Sept. 9, 2025, 5:29 p.m.