ri_test2

Example data for testing the need for a random intercept. LRT results show that a random slope is not warranted.

datasets

Convenience functions and datasets to be used with Practical Multilevel Modeling using R. The package includes functions for calculating group means, group mean centered variables, and displaying some basic missing data information. A function for computing robust standard errors for linear mixed models based on Liang and Zeger (1986) <doi:10.1093/biomet/73.1.13> and Bell and 'McCaffrey' (2002) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2002002/article/9058-eng.pdf?st=NxMjN1YZ> is included as well as a function for checking for level-one homoskedasticity (Raudenbush & Bryk, 2002, ISBN:076191904X).

Francis Huang

MLMusingR

Practical Multilevel Modeling

ri_test2 function

A data frame with 3,000 observations from 30 groups and 4 variables:<dl>
 <dt>y</dt>
<dd>The outcome variable.</dd> <dt>w1</dt>
<dd>A level-2 predictor.</dd> <dt>x1</dt>
<dd>A level-1 predictor</dd> <dt>group</dt>
<dd>The cluster identifier</dd>
</dl>

Format

Sample dataset 2 for testing the likelihood ratio test (LRT) — ri_test2

A data frame with 3,000 observations from 30 groups and 4 variables:<dl>
 <dt>y</dt>
<dd>The outcome variable.</dd>

 <dt>w1</dt>
<dd>A level-2 predictor.</dd>

 <dt>x1</dt>
<dd>A level-1 predictor</dd>

 <dt>group</dt>
<dd>The cluster identifier</dd>


</dl>

ri_test2: Sample dataset 2 for testing the likelihood ratio test (LRT)

Description

Usage

Arguments

Format