cross_class

Number of cross classified ids to generate.

num_ids

Sample size to generate, this is used to pass to the 
<code><a rd-options="" href="/link/sample?package=simglm&version=0.8.0" data-mini-rdoc="simglm::sample">sample</a></code> function.

samp_size

A list of data generating characteristics used to generate
 the cross classified random effect. This function needs to include:<ul>
<li>random_var The variance of the cross classified random effect.</li>
<li>rand_gen The random generating function used.</li>
</ul>Optional elements are:<ul>
<li>ther: Theorectial mean and variance from rand_gen,</li>
<li>ther_sim: Simulate mean/variance for standardization purposes,</li>
<li>cor_vars: Correlation between random effects,</li>
<li>...: Additional parameters needed for rand_gen function.</li>
</ul>See <code><a rd-options="" href="/link/sim_rand_eff?package=simglm&version=0.8.0" data-mini-rdoc="simglm::sim_rand_eff">sim_rand_eff</a></code> for additional parameters that can be passed.

random_param

Input cross classified simulation parameters, output cross classified structure
as a function of the original id variables. This function currently only supports
a single (intercept) cross classified random effect.

Simulates regression models,
including both simple regression and generalized linear mixed
models with up to three level of nesting. Power simulations that are
flexible allowing the specification of missing data, unbalanced designs,
and different random error distributions are built into the package.

Brandon LeBeau

simglm

Simulate Models Based on the Generalized Linear Model

cross_class function

Sample size to generate, this is used to pass to the 
<code><a rd-options='' href='sample'>sample</a></code> function.

A list of data generating characteristics used to generate
 the cross classified random effect. This function needs to include:<ul>
<li>random_var The variance of the cross classified random effect.</li>
<li>rand_gen The random generating function used.</li>
</ul>Optional elements are:<ul>
<li>ther: Theorectial mean and variance from rand_gen,</li>
<li>ther_sim: Simulate mean/variance for standardization purposes,</li>
<li>cor_vars: Correlation between random effects,</li>
<li>...: Additional parameters needed for rand_gen function.</li>
</ul>See <code><a rd-options='' href='sim_rand_eff'>sim_rand_eff</a></code> for additional parameters that can be passed.

cross_class: Cross Classified Generation

Description

Usage

Arguments