is.outside_CI

Returns <code>TRUE</code> if parameter reflecting a null hypothesis
falls outside a given confidence interval. This is an alternative approach
to writing an experiment that returns a p-value.

Provides a general purpose simulation-based power analysis
API for routine and customized simulation experimental designs.
The package focuses exclusively on Monte Carlo simulation experiment variants of
(expected) prospective power analyses,
criterion analyses, compromise analyses, sensitivity analyses, and
a priori/post-hoc analyses. The default simulation experiment functions defined within the package
provide stochastic variants of the power analysis subroutines in
G*Power 3.1 (Faul, Erdfelder, Buchner, and Lang, 2009) <doi:10.3758/brm.41.4.1149>,
along with various other parametric and non-parametric power analysis
applications (e.g., mediation analyses) and support for Bayesian power analysis
by way of Bayes factors or posterior probability evaluations.
Additional functions for building
empirical power curves, reanalyzing simulation information, and
for increasing the precision of the resulting power
estimates are also included, each of which utilize similar API structures. For
further details see the associated publication in
Chalmers (2025) <doi:10.3758/s13428-025-02787-z>.

Phil Chalmers

Spower

Power Analyses using Monte Carlo Simulations

is.outside_CI function

<dl><dt>P0</dt>
<dd>parameter to evaluate</dd>
<dt>CI</dt>
<dd>confidence interval</dd></dl>

Arguments

Phil Chalmers <a href="/link/rphilip.chalmers%40gmail.com?package=Spower&version=0.6" data-mini-rdoc="Spower::rphilip.chalmers@gmail.com">rphilip.chalmers@gmail.com</a>

Author

Evaluate whether parameter is outside a given confidence interval — is.outside_CI

<dl>

<dt>P0</dt>
<dd>parameter to evaluate</dd>


<dt>CI</dt>
<dd>confidence interval</dd>

</dl>

Phil Chalmers <a href='mailto:rphilip.chalmers@gmail.com'>rphilip.chalmers@gmail.com</a>

is.outside_CI: Evaluate whether parameter is outside a given confidence interval

Description

Usage

Value

Arguments

Author

See Also

Examples