MyLM

Primarily devoted to implementing the Univariate Bootstrap (as well as the Traditional Bootstrap). In addition there are multiple functions for DeFries-Fulker behavioral genetics models. The univariate bootstrapping functions, DeFries-Fulker functions, regression and traditional bootstrapping functions form the original core. Additional features may come online later, however this software is a work in progress. For more information about univariate bootstrapping see: Lee and Rodgers (1998) and Beasley et al (2007) <doi:10.1037/1082-989X.12.4.414>.

Patrick O'Keefe

Omisc

Univariate Bootstrapping and Other Things

MyLM function

<dl><dt>Y</dt>
<dd>The Y variable</dd>
<dt>X</dt>
<dd>A matrix of X variables</dd>
<dt>robust</dt>
<dd>Should robust standard errors be calculated? Assumes a double entered twin dataset with twins evenly spaced in the dataset.</dd>
<dt>betasonly</dt>
<dd>Should only the betas be returned? Good for bootstrapping</dd>
<dt>typicalSE</dt>
<dd>Should the typical standard errors be included? Default is true. Can be true when robust is True.</dd></dl>

Arguments

MyLM — MyLM

<dl>

<dt>Y</dt>
<dd>The Y variable</dd>


<dt>X</dt>
<dd>A matrix of X variables</dd>


<dt>robust</dt>
<dd>Should robust standard errors be calculated? Assumes a double entered twin dataset with twins evenly spaced in the dataset.</dd>


<dt>betasonly</dt>
<dd>Should only the betas be returned? Good for bootstrapping</dd>


<dt>typicalSE</dt>
<dd>Should the typical standard errors be included? Default is true. Can be true when robust is True.</dd>

</dl>

MyLM: MyLM

Description

Usage

Value

Arguments

Examples