print.powRICLPM

<code>print.powRICLPM</code> prints a table listing all experimental conditions contained in the <code>powRICLPM</code> object, as well as the frequency of the estimation problems that occurred in each.

Perform user-friendly power analyses for the bivariate random
intercept cross-lagged panel model (RI-CLPM). The strategy as proposed
by Mulder (2022) <doi:10.1080/10705511.2022.2122467> is implemented.
Extended power analysis options include the use of bounded estimation,
inclusion of measurement error in the data generating model and
estimation model (i.e., the stable trait autoregressive trait state,
STARTS, model), imposing various constraints over time on the
parameters of the estimation model, among others.

Jeroen Mulder

powRICLPM

Perform Power Analysis for the Random Intercept Cross-Lagged
Panel Model

Netherlands Organization for Scientific Research 

print.powRICLPM function

<dl><dt>x</dt>
<dd>A <code>powRICLPM</code> object.</dd>
<dt>...</dt>
<dd>Argument not in use.</dd></dl>

Arguments

Print powRICLPM object — print.powRICLPM

<dl>

<dt>x</dt>
<dd>A <code>powRICLPM</code> object.</dd>


<dt>...</dt>
<dd>Argument not in use.</dd>

</dl>

print.powRICLPM: Print `powRICLPM` object

Description

Usage

Value

Arguments