mvregmed.dat.check

regmed.dat.check

Assure that x, y, mediator are matrices, check column names and fill in
if NULL, and reduce x, y, mediator so no missing values among all three matrices.

 models

Mediation analysis for multiple mediators by penalized structural equation models with different types of penalties depending on whether there are multiple mediators and only one exposure and one outcome variable (using sparse group lasso) or multiple exposures, multiple mediators, and multiple outcome variables (using lasso, L1, penalties).

Jason Sinnwell

regmed

Regularized Mediation Analysis

Daniel Schaid

mvregmed.dat.check function

<dl> <dt>x</dt>
<dd>matrix with columns representing "exposure" variable (sometimes called instrumental variable)</dd> <dt>y</dt>
<dd>matrix with columns representing outcome variables</dd> <dt>mediator</dt>
<dd>matrix with columns representing mediator variables</dd> <dt>max.cor</dt>
<dd>maximum correlation within y, x, or mediators, so fitting is more robust</dd></dl>

Arguments

Author

Helper function to check x, y, mediator for input to mvregmed functions — mvregmed.dat.check

<dl>

 <dt>x</dt>
<dd>matrix with columns representing "exposure" variable (sometimes called instrumental variable)</dd>

 <dt>y</dt>
<dd>matrix with columns representing outcome variables</dd>

 <dt>mediator</dt>
<dd>matrix with columns representing mediator variables</dd>

 <dt>max.cor</dt>
<dd>maximum correlation within y, x, or mediators, so fitting is more robust</dd>

</dl>

mvregmed.dat.check: Helper function to check x, y, mediator for input to mvregmed functions

Description

Usage

Value

Arguments

Author

See Also