z_to_power

A function for computing power of two-sided tests
corresponding to z-scores for a given significance level.
<code>alpha</code> (or corresponding cut-off z-score <code>a</code>)

An implementation of z-curves - a method for estimating expected discovery
and replicability rates on the bases of test-statistics of published studies. The package
provides functions for fitting the new density and EM version
(Bartoš & Schimmack, 2020, <doi:10.31234/osf.io/urgtn>), censored observations,
as well as the original density z-curve (Brunner & Schimmack, 2020, <doi:10.15626/MP.2018.874>).
Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects.
See the aforementioned articles for more information about the z-curves, expected discovery
and replicability rates, validation studies, and limitations.

Franti<c5><a1>ek Barto<c5><a1>

zcurve

An Implementation of Z-Curves

František Bartoš

Ulrich Schimmack

z_to_power function

<dl><dt>z</dt>
<dd>A vector of z-scores</dd>
<dt>alpha</dt>
<dd>Level of significance alpha</dd>
<dt>a</dt>
<dd>Or, alternatively a z-score corresponding to <code>alpha</code></dd>
<dt>two.sided</dt>
<dd>Whether directionality of the effect size should be taken into account.</dd></dl>

Arguments

Compute power corresponding to z-scores — z_to_power

<dl>

<dt>z</dt>
<dd>A vector of z-scores</dd>


<dt>alpha</dt>
<dd>Level of significance alpha</dd>


<dt>a</dt>
<dd>Or, alternatively a z-score corresponding to <code>alpha</code></dd>


<dt>two.sided</dt>
<dd>Whether directionality of the effect size should be taken into account.</dd>

</dl>

z_to_power: Compute power corresponding to z-scores

Description

Usage

Arguments

Examples