Learn R Programming

OpenMx (version 2.7.9)

HS.ability.data:

Description

This classic data set contains of intelligence-test scores from 301 children on 26 distinct tests. The data are also available in the MBESS package. The tests cover mental speed, memory, mathematical-ability, spatial, and verbal ability as listed below.

Usage

data("HS.ability.data")

Arguments

Format

A data frame with 301 observations on the following 2 variables.
id
student ID number (int)
Gender
Sex (Factor w/ 2 levels “Female”,“Male”
grade
Grade in school (integer 7 or 8)
agey
Age in years (integer)
agem
Age in months (integer)
school
School attended (Factor w/2 levels “Grant-White” and “Pasteur”)
addition
A speed test (numeric)
code
A speed test (numeric)
counting
A speed test (numeric)
straight
A speed test (numeric)
wordr
A memory subtest
numberr
A memory subtest
figurer
A memory subtest
object
A memory subtest
numberf
A memory subtest
figurew
A memory subtest
deduct
A mathematical subtest
numeric
A mathematical subtest
problemr
A mathematical subtest
series
A mathematical subtest
arithmet
A mathematical subtest
visual
A spatial subtest
cubes
A spatial subtest
paper
A spatial subtest
flags
A spatial subtest
paperrev
A spatial subtest
flagssub
A spatial subtest
general
A verbal subtest
paragrap
A verbal subtest
sentence
A verbal subtest
wordc
A verbal subtest
wordm
A verbal subtest

Details

The data are from children who differ in grade (seventh- and eighth-grade) and are nested in one of two schools (Pasteur and Grant-White). You will see it in use elsewhere, both in R (lavaan, MBESS), and in Joreskog (1969) reporting a cfa on the Grant-White school subject subset). The last two tests are substitute versions for other tests. paperrev (a paper form board test) can substitute for paper and flagssub for the lozenges test flags.

References

Holzinger, K., and Swineford, F. (1939). A study in factor analysis: The stability of a bifactor solution. Supplementary Educational Monograph, no. 48. Chicago: University of Chicago Press. Joreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34, 183-202.

Examples

Run this code
data(HS.ability.data)
str(HS.ability.data)
levels(HS.ability.data$school)
plot(flags ~ flagssub, data = HS.ability.data)

Run the code above in your browser using DataLab