interval_toIntegrate2 {bpp} | R Documentation |
Product of posterior density and conditional power for blinded interim result
Description
Product of posterior density and conditional power for two blinded interim results, integrate over this function to get BPP.
Usage
interval_toIntegrate2(x, prior = "normal", interimSE, finalSE, successmean,
IntEffBoundary, IntFutBoundary, priormean, ...)
Arguments
x |
Value at which to evaluate the function. |
prior |
Prior density on effect sizes. |
interimSE |
(Known) standard error of |
finalSE |
(Known) standard error at which the final analysis of the study under consideration takes place. |
successmean |
The mean that defines success at the final analysis. Typically chosen to be the minimal detectable difference, i.e. the critical on the scale of the effect size of interest corresponding to the significance level at the final analysis. |
IntEffBoundary |
Efficacy boundary at the interim analysis. |
IntFutBoundary |
Futility boundary at the interim analysis. |
priormean |
Prior mean. |
... |
Further arguments specific to the chosen prior (see |
Value
Value of the function, a real number.
Author(s)
Kaspar Rufibach (maintainer)
kaspar.rufibach@roche.com
References
Rufibach, K., Jordan, P., Abt, M. (2016a). Sequentially Updating the Likelihood of Success of a Phase 3 Pivotal Time-to-Event Trial based on Interim Analyses or External Information. J. Biopharm. Stat., 26(2), 191–201.
Examples
# type ?bpp_2interim for code of all the computations in Rufibach et al (2016a).