powered by
If we update the prior with a known estimate at an interim analysis, we get a density that is proportional to the value of this function.
estimate_posterior_nominator(x, prior = c("normal", "flat"), interimmean, interimSE, priormean, ...)
Value of the function, a real number.
Value at which to evaluate the function.
Prior density on effect sizes.
Mean of the data.
(Known) standard error of interimmean.
interimmean
Prior mean.
Further arguments specific to the chosen prior (see bpp for examples).
bpp
Kaspar Rufibach (maintainer) kaspar.rufibach@roche.com
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.
# type ?bpp_1interim for code of all the computations in Rufibach et al (2016a).
Run the code above in your browser using DataLab