For a multisite replication project, computes the consistency metric P_orig, which is
    the probability that the original study would observe an estimated effect size as extreme or more extreme
    than it actually did, if in fact the original study were statistically consistent with the replications. Other
    recommended metrics are: (1) the probability of a true effect of scientifically meaningful size in the same direction as the estimate
    the original study; and (2) the probability of a true effect of meaningful size in the direction opposite
    the original study's estimate. These two can be computed using the package \code{MetaUtility::prop_stronger}.
    Additionally computes older metrics used in replication projects (namely expected agreement in "statistical significance" between an original study and replication studies as well
    as prediction intervals for the replication estimates). See Mathur and VanderWeele (under review; <https://osf.io/apnjk/>)
    for details.

Performs comparative bioavailability calculations for Average
    Bioequivalence with Expanding Limits (ABEL). Implemented are 'Method A' /
    'Method B' and the detection of outliers. If the design allows, assessment
    of the empiric Type I Error and iteratively adjusting alpha to control the
    consumer risk. Average Bioequivalence - optionally with a tighter (narrow
    therapeutic index drugs) or wider acceptance range (South Africa: Cmax) -
    is implemented as well.

Test for effects of  both individual factors and their interaction on  replicated spatial patterns in a two factorial design, as explained in Ramon et al. (2016) <doi:10.1111/ecog.01848>.

Provides utilities for the design and analysis of replication
    studies.  Features both traditional methods based on statistical
    significance and more recent methods such as the sceptical p-value;
    Held L. (2020) <doi:10.1111/rssa.12493>, Held et al. (2022)
    <doi:10.1214/21-AOAS1502>, Micheloud et al. (2023) <doi:10.1111/stan.12312>.
    Also provides related methods including the harmonic mean chi-squared
    test; Held, L. (2020) <doi:10.1111/rssc.12410>, and intrinsic
    credibility; Held, L. (2019) <doi:10.1098/rsos.181534>. Contains
    datasets from five large-scale replication projects.