slcaControl

Control Parameters for slca Estimation

Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including
Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) <doi:10.1002/9780470567333>,
Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) <doi:10.1111/j.1467-985x.2010.00674.x>, and
Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) <doi:10.1080/10705511.2017.1340844>, and
any other extended models involving multiple latent class variables.

Youngsun Kim

slca

Structural Modeling for Multiple Latent Class Variables

Hwan Chung

slcaControl function

<dl><dt>em.iterlim</dt>
<dd>an integer specifying maximum number of iterations allowed for EM algorithm. Default is 3000.</dd>
<dt>em.tol</dt>
<dd>a numeric value setting tolerance for the convergence of EM algorithm. Default is 1e-6.</dd>
<dt>nlm.iterlim</dt>
<dd>an integer specifying maximum number of iterations allowed for estimation with <code>nlm</code> function. Default is 1000.</dd>
<dt>nlm.tol</dt>
<dd>a numeric value setting tolerance for the convergence of <code>nlm</code> function. Default is 1e-8.</dd>
<dt>init.param</dt>
<dd>initial parameters.</dd>
<dt>nrep</dt>
<dd>number of trials. Default is 1.</dd>
<dt>test.iter</dt>
<dd>an integer specifying maximum number of iterations allowed for testing parameters. Default is 200</dd>
<dt>na.rm</dt>
<dd>a logical value indicating whether to remove observations including missing values (NA)</dd>
<dt>verbose</dt>
<dd>a logical value indicating whether to display progress updates during the estimation process</dd></dl>

Arguments

Control Parameters for slca Estimation — slcaControl

<dl>

<dt>em.iterlim</dt>
<dd>an integer specifying maximum number of iterations allowed for EM algorithm. Default is 3000.</dd>


<dt>em.tol</dt>
<dd>a numeric value setting tolerance for the convergence of EM algorithm. Default is 1e-6.</dd>


<dt>nlm.iterlim</dt>
<dd>an integer specifying maximum number of iterations allowed for estimation with <code>nlm</code> function. Default is 1000.</dd>


<dt>nlm.tol</dt>
<dd>a numeric value setting tolerance for the convergence of <code>nlm</code> function. Default is 1e-8.</dd>


<dt>init.param</dt>
<dd>initial parameters.</dd>


<dt>nrep</dt>
<dd>number of trials. Default is 1.</dd>


<dt>test.iter</dt>
<dd>an integer specifying maximum number of iterations allowed for testing parameters. Default is 200</dd>


<dt>na.rm</dt>
<dd>a logical value indicating whether to remove observations including missing values (NA)</dd>


<dt>verbose</dt>
<dd>a logical value indicating whether to display progress updates during the estimation process</dd>

</dl>

slcaControl: Control Parameters for slca Estimation

Description

Usage

Value

Arguments

See Also