assurance.multiple.endpoints: Compute Assurance for Multiple Correlated Endpoints

assurance.multiple.endpointsR Documentation

Compute Assurance for Multiple Correlated Endpoints

Description

These generic functions provide the framework for assurance computations for trials with multiple endpoints.

Arguments

earlyStudy

Data defining the initial study.

laterStudy

Information about the later study.

nsim

Number of Monte-Carlo simulations (maybe unnecessary).

posteriorSample

A sample from our posterior distribution.

laterSample

Simulations of the later trial.

Details

These generic functions tie together the whole assurance calculation for multiple endpoints. By default they do Monte-Carlo simulation using samplePosterior (which samples from the posterior distribution), sampleLater (which, given a sample from the posterior, simulates the later study), and sampleAndTestLater. sampleAndTestLater is just the composition of samplePosterior and testLater.

sampleAndTestLater exists for the purposes of shortcut calculations in which, given a sample from the posterior, the probability of later stage success can be directly determined.

Value

assurance.multiple.endpoints returns a list of items: NoAdjustment.Each returns (uncorrected) assurance values for each endpoint separately. NoAdjustment.AtLeastOne returns the (uncorrected) assurance that at least one endpoint will be statistically significant. NoAdjustmentAll returns the (uncorrected) assurance that all endpoints will be statistically significant. Currently no multiplicity adjustments are implemented.

samplePosterior returns an opaque object that contains samples from the posterior.

sampleLater returns an opaque object that contains simulated results for the later study.

testLater returns probability of success for the simulated later study.

sampleAndTestLater returns probability of success for simulated later study.

Author(s)

Paul Metcalfe, Mary Jenner, Daniel Dalevi


scientific-computing-solutions/assurance documentation built on June 28, 2023, 12:31 p.m.