pvalueBound

Necessary or sufficient bounds for significance of the harmonic mean
chi-squared test are computed for n one-sided p-values.

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.

Samuel Pawel

ReplicationSuccess

Design and Analysis of Replication Studies

Leonhard Held

Charlotte Micheloud

Florian Gerber

Felix Hofmann

pvalueBound function

<dl><dt>alpha</dt>
<dd>Numeric vector specifying the significance level.</dd>
<dt>n</dt>
<dd>The number of p-values.</dd>
<dt>type</dt>
<dd>Either "necessary" (default) or "sufficient".
If "necessary", the necessary bounds are computed.
If "sufficient", the sufficient bounds are computed.</dd></dl>

Arguments

Author

Bound for the p-values entering the harmonic mean chi-squared test — pvalueBound

<dl>

<dt>alpha</dt>
<dd>Numeric vector specifying the significance level.</dd>


<dt>n</dt>
<dd>The number of p-values.</dd>


<dt>type</dt>
<dd>Either "necessary" (default) or "sufficient".
If "necessary", the necessary bounds are computed.
If "sufficient", the sufficient bounds are computed.</dd>

</dl>

pvalueBound: Bound for the p-values entering the harmonic mean chi-squared test

Description

Usage

Value

Arguments

Author

References

See Also

Examples