Math

A dataset containing the mothers' education level, children's mathematical achievement
and other attributes of 76 families.

datasets

Methods for mediation analysis with missing data and non-normal data are implemented. For missing data, four methods are available: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included to handle missing data. For handling non-normal data, bootstrap and two-stage robust methods can be used. Technical details of the methods can be found in Zhang and Wang (2013, <doi:10.1007/s11336-012-9301-5>), Zhang (2014, <doi:10.3758/s13428-013-0424-0>), and Yuan and Zhang (2012, <doi:10.1007/s11336-012-9282-4>).

Zhiyong Zhang

bmemLavaan

Mediation Analysis with Missing Data and Non-Normal Data

Shuigen Ming

Hong Zhang

Lijuan Wang

Math function

A data frame with 76 observations on the following 4 variables.<dl>
 <dt>ME</dt>
<dd>mothers' education level</dd> <dt>HE</dt>
<dd>home environment</dd> <dt>MATH</dt>
<dd>children's mathematical achievement</dd> <dt>READ</dt>
<dd>reading recognition ability</dd> 
</dl>

Format

Parents' education levels and adolescent mathematics achievement of 76 families in 1986 — Math

A data frame with 76 observations on the following 4 variables.<dl>
 <dt>ME</dt>
<dd>mothers' education level</dd>

 <dt>HE</dt>
<dd>home environment</dd>

 <dt>MATH</dt>
<dd>children's mathematical achievement</dd>

 <dt>READ</dt>
<dd>reading recognition ability</dd>

 
</dl>

Math: Parents' education levels and adolescent mathematics achievement of 76 families in 1986

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