setupPrepPaths

Allows user to open and close certain paths.

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

setupPrepPaths function

<dl><dt>paths</dt>
<dd><code>lavaan</code>-style syntax containing paths with which
to begin model estimation (optional). That is, Y~X indicates that Y
is regressed on X, or X predicts Y. If no header is used,
then variables should be referred to with V followed (with no separation)
by the column number. If a header is used, variables should be referred to using 
variable names. To reference lag variables, "lag" should be added to the 
end of the variable name with no separation. Defaults to NULL.</dd></dl>

Arguments

Allows user to open and close certain paths. — setupPrepPaths

<dl>

<dt>paths</dt>
<dd><code>lavaan</code>-style syntax containing paths with which
to begin model estimation (optional). That is, Y~X indicates that Y
is regressed on X, or X predicts Y. If no header is used,
then variables should be referred to with V followed (with no separation)
by the column number. If a header is used, variables should be referred to using 
variable names. To reference lag variables, "lag" should be added to the 
end of the variable name with no separation. Defaults to NULL.</dd>

</dl>

setupPrepPaths: Allows user to open and close certain paths.

Description

Usage

Arguments