mp_parameters

An S3 class that contains an <code><a href="/link/base%3A%3Aenvironment?package=mlmpower&version=1.0.9" data-mini-rdoc="mlmpower::base::environment">base::environment</a></code> with the following objects:<ul>
<li><code>r2</code>: The population proportion of variance explained</li>
<li><code>phi_b</code>: The population predictor covariance matrix for between</li>
<li><code>phi_p</code>: The population within cluster covariance matrix for products</li>
<li><code>phi_w</code>: The population predictor covariance matrix for within</li>
<li><code>mean_Z</code>: The population mean for level-2 predictors</li>
<li><code>mean_X</code>: The population mean for level-1 predictors</li>
<li><code>var_e</code>: The population within residual variance</li>
<li><code>tau</code>: The population level-2 covariance matrix</li>
<li><code>gammas</code>: The regression coefficients</li>
<li><code>mean_Y</code>: The population mean of the outcome</li>
</ul>

A declarative language for specifying multilevel models,
solving for population parameters based on specified variance-explained effect
size measures, generating data, and conducting power analyses to determine
sample size recommendations. The specification allows for any number of
within-cluster effects, between-cluster effects, covariate effects
at either level, and random coefficients. Moreover, the models do not
assume orthogonal effects, and predictors can correlate at either level
and accommodate models with multiple interaction effects.

Brian T. Keller

mlmpower

Power Analysis and Data Simulation for Multilevel Models

mp_parameters function

An S3 class that contains an <code><a href='https://rdrr.io/r/base/environment.html'>base::environment</a></code> with the following objects:<ul>
<li><code>r2</code>: The population proportion of variance explained</li>
<li><code>phi_b</code>: The population predictor covariance matrix for between</li>
<li><code>phi_p</code>: The population within cluster covariance matrix for products</li>
<li><code>phi_w</code>: The population predictor covariance matrix for within</li>
<li><code>mean_Z</code>: The population mean for level-2 predictors</li>
<li><code>mean_X</code>: The population mean for level-1 predictors</li>
<li><code>var_e</code>: The population within residual variance</li>
<li><code>tau</code>: The population level-2 covariance matrix</li>
<li><code>gammas</code>: The regression coefficients</li>
<li><code>mean_Y</code>: The population mean of the outcome</li>
</ul>

mp_parameters: `mp_parameters` Object for `mlmpower`

Description

Arguments

See Also