estimate_posterior: Posterior density conditional on known interim result

In bpp: Computations Around Bayesian Predictive Power

Description

If we update the prior with a known estimate at an interim analysis, we get this density.

Usage

estimate_posterior(x, prior = c("normal", "flat"), interimmean, interimSE, priormean, ...)

Arguments

x	Value at which to evaluate the function.
prior	Prior density on effect sizes.
interimmean	Mean of the data.
interimSE	(Known) standard error of interimmean.
priormean	Prior mean.
...	Further arguments specific to the chosen prior (see bpp for examples).

Value

Value of the function, a real number.

Author(s)

Kaspar Rufibach (maintainer)
[e-mail]

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_1interim for code of all the computations in Rufibach et al (2016a).

bpp documentation built on Jan. 13, 2022, 5:09 p.m.