HS9Var

Mental abilities data on seventh- and eighth-grade children from the classic
Holzinger and Swineford (1939) dataset.

datasets

Computes fungible coefficients and Monte Carlo data. Underlying theory for these functions is described in the following publications:
Waller, N. (2008). Fungible Weights in Multiple Regression. Psychometrika, 73(4), 691-703, <DOI:10.1007/s11336-008-9066-z>.
Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights.
Psychometrika, 74(4), 589-602, <DOI:10.1007/s11336-008-9087-7>.
Waller, N. G. (2016). Fungible Correlation Matrices:
A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for
Monte Carlo Research. Multivariate Behavioral Research, 51(4), 554-568, <DOI:10.1080/00273171.2016.1178566>.
Jones, J. A. & Waller, N. G. (2015). The normal-theory and asymptotic distribution-free (ADF)
covariance matrix of standardized regression coefficients: theoretical extensions
and finite sample behavior. Psychometrika, 80, 365-378, <DOI:10.1007/s11336-013-9380-y>.
Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. <DOI:10.1007/s11336-017-9599-0>.

Niels G Waller

fungible

Psychometric Functions from the Waller Lab

Niels Waller

Jeff Jones

Casey Giordano

HS9Var function

A data frame with 301 observations on the following 15 variables.<dl>
<dt>id</dt>
<dd>subject identifier</dd>
 <dt>sex</dt>
<dd>gender</dd><dt>ageyr</dt>
<dd>age, year part</dd>
 <dt>agemo</dt>
<dd>age, month part</dd><dt>school</dt>
<dd>school name (Pasteur or Grant-White)</dd>
 <dt>grade</dt>
<dd>grade</dd><dt>x1</dt>
<dd>Visual perception</dd>
 <dt>x2</dt>
<dd>Cubes</dd>
 <dt>x3</dt>
<dd>Lozenges</dd><dt>x4</dt>
<dd>Paragraph comprehension</dd>
 <dt>x5</dt>
<dd>Sentence completion</dd><dt>x6</dt>
<dd>Word meaning</dd>
 <dt>x7</dt>
<dd>Speeded addition</dd>
 <dt>x8</dt>
<dd>Speeded
counting of dots</dd>
 <dt>x9</dt>
<dd>Speeded discrimination straight and curved
capitals</dd>
 
</dl>

Format

9 Variables from the Holzinger and Swineford (1939) Dataset — HS9Var

A data frame with 301 observations on the following 15 variables.<dl>
<dt>id</dt>
<dd>subject identifier</dd>
 <dt>sex</dt>
<dd>gender</dd>

<dt>ageyr</dt>
<dd>age, year part</dd>
 <dt>agemo</dt>
<dd>age, month part</dd>

<dt>school</dt>
<dd>school name (Pasteur or Grant-White)</dd>
 <dt>grade</dt>
<dd>grade</dd>

<dt>x1</dt>
<dd>Visual perception</dd>
 <dt>x2</dt>
<dd>Cubes</dd>
 <dt>x3</dt>
<dd>Lozenges</dd>

<dt>x4</dt>
<dd>Paragraph comprehension</dd>
 <dt>x5</dt>
<dd>Sentence completion</dd>

<dt>x6</dt>
<dd>Word meaning</dd>
 <dt>x7</dt>
<dd>Speeded addition</dd>
 <dt>x8</dt>
<dd>Speeded
counting of dots</dd>
 <dt>x9</dt>
<dd>Speeded discrimination straight and curved
capitals</dd>
 
</dl>

HS9Var: 9 Variables from the Holzinger and Swineford (1939) Dataset

Description

Arguments

Format

References

Examples