summary.Method

This function summarizes the objects of class <code>Method</code> and provides
information about the method run and the sample size recommendation.

An implementation of the sample size computation method for network
models proposed by Constantin et al. (2021) <doi:10.31234/osf.io/j5v7u>.
The implementation takes the form of a three-step recursive algorithm
designed to find an optimal sample size given a model specification and a
performance measure of interest. It starts with a Monte Carlo simulation
step for computing the performance measure and a statistic at various sample
sizes selected from an initial sample size range. It continues with a
monotone curve-fitting step for interpolating the statistic across the entire
sample size range. The final step employs stratified bootstrapping to quantify
the uncertainty around the fitted curve.

Mihai Constantin

powerly

Sample Size Analysis for Psychological Networks and More

summary.Method function

<dl><dt>object</dt>
<dd>An object instance of class <code>Method</code>.</dd>
<dt>...</dt>
<dd>Other optional arguments currently not in use.</dd></dl>

Arguments

Provide a summary of the sample size analysis results — summary.Method

<dl>

<dt>object</dt>
<dd>An object instance of class <code>Method</code>.</dd>


<dt>...</dt>
<dd>Other optional arguments currently not in use.</dd>

</dl>

summary.Method: Provide a summary of the sample size analysis results

Description

Usage

Arguments

See Also