lowest.z

Identifies lowest z value from list of z values.

internal

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

lowest.z function

<dl><dt>z_list</dt>
<dd>A list of z values across individuals.</dd>
<dt>elig_paths</dt>
<dd>A character vector containing eligible paths that
gimme is allowed to drop from the model at a given stage.</dd>
<dt>prop_cutoff</dt>
<dd>The proportion of individuals for whom a path must be
nonsignificant in order for it to be dropped from the models. NULL if used 
at the individual-level.</dd>
<dt>n_subj</dt>
<dd>The number of subjects in a given stage of the search. If
in the group stage, n_subj equals the number of subjects. If in the subgroup
stage, n_subj equals the number of individuals in a given subgroup. At the 
individual stage, n_subj = 1.</dd></dl>

Arguments

Identifies lowest z value from list of z values. — lowest.z

<dl>

<dt>z_list</dt>
<dd>A list of z values across individuals.</dd>


<dt>elig_paths</dt>
<dd>A character vector containing eligible paths that
gimme is allowed to drop from the model at a given stage.</dd>


<dt>prop_cutoff</dt>
<dd>The proportion of individuals for whom a path must be
nonsignificant in order for it to be dropped from the models. NULL if used 
at the individual-level.</dd>


<dt>n_subj</dt>
<dd>The number of subjects in a given stage of the search. If
in the group stage, n_subj equals the number of subjects. If in the subgroup
stage, n_subj equals the number of individuals in a given subgroup. At the 
individual stage, n_subj = 1.</dd>

</dl>

lowest.z: Identifies lowest z value from list of z values.

Description

Usage

Value

Arguments