This function computes the marginal likelihood of the
replication effect estimate tr under the power prior model
$$f(\code{tr}|\code{to}, \code{so}, \code{sr}, \code{x}, \code{y}) =
\int_0^1 \int_{-\infty}^{\infty} \mathrm{N}(\code{tr}; \theta,
\code{sr}^2) \times \mathrm{N}(\theta; \mu, \phi)
\times \mbox{Beta}(\alpha; \code{x}, \code{y}) ~\mbox{d}\theta~
\mbox{d}\alpha$$ with \(\phi = 1/(1/\code{v} +
\alpha/\code{so}^2)\) and \(\mu =
\phi\{(\alpha\times\code{to})/\code{so}^2 + \code{m}/\code{v}\}\) using numerical integration.
margLik(tr, to, sr, so, x = 1, y = 1, m = 0, v = Inf, ...)Marginal likelihood
Effect estimate of the replication study.
Effect estimate of the original study.
Standard error of the replication effect estimate.
Standard error of the replication effect estimate.
Number of successes parameter of beta prior for \(\alpha\).
Defaults to 1.
Number of failures parameter of beta prior for \(\alpha\).
Defaults to 1.
Mean parameter of initial normal prior for \(\theta\).
Defaults to 0.
Variance parameter of initial normal prior for \(\theta\).
Defaults to Inf (uniform prior).
Additional arguments passed to stats::integrate.
Samuel Pawel