recode.vars

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

recode.vars function

<dl><dt>data</dt>
<dd>The vector of variable names to be recoded</dd>
<dt>oldvalue</dt>
<dd>A vector containing the latent variable names used internally.</dd>
<dt>newvalue</dt>
<dd>A vector containing the observed variable names, either
provided by the user (as a header) or provided by R (e.g., V1, V2).</dd></dl>

Arguments

Recode variable names. — recode.vars

<dl>

<dt>data</dt>
<dd>The vector of variable names to be recoded</dd>


<dt>oldvalue</dt>
<dd>A vector containing the latent variable names used internally.</dd>


<dt>newvalue</dt>
<dd>A vector containing the observed variable names, either
provided by the user (as a header) or provided by R (e.g., V1, V2).</dd>

</dl>

Last chance! 50% off unlimited learning

recode.vars: Recode variable names.

Description

Usage

Value

Arguments