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Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.

KM Gates

gimme

Group Iterative Multiple Model Estimation

final.org function

<dl><dt>dat</dt>
<dd>A list containing information created in setup().</dd>
<dt>grp</dt>
<dd>A list containing group-level information. NULL in aggSEM and
indSEM.</dd>
<dt>sub</dt>
<dd>A list containing subgroup information.</dd>
<dt>sub_spec</dt>
<dd>A list containing information specific to each subgroup.</dd>
<dt>store</dt>
<dd>A list containing output from indiv.search().</dd></dl>

Arguments

Wrapup, create output files. — final.org

<dl>

<dt>dat</dt>
<dd>A list containing information created in setup().</dd>


<dt>grp</dt>
<dd>A list containing group-level information. NULL in aggSEM and
indSEM.</dd>


<dt>sub</dt>
<dd>A list containing subgroup information.</dd>


<dt>sub_spec</dt>
<dd>A list containing information specific to each subgroup.</dd>


<dt>store</dt>
<dd>A list containing output from indiv.search().</dd>

</dl>

final.org: Wrapup, create output files.

Description

Usage

Value

Arguments