Holzinger and Swineford Dataset (9 Variables)

The classic Holzinger and Swineford (1939) dataset consists of mental ability test scores of seventh- and eighth-grade children from two different schools (Pasteur and Grant-White). In the original dataset (available in the MBESS package), there are scores for 26 tests. However, a smaller subset with 9 variables is more widely used in the literature (for example in Joreskog's 1969 paper, which also uses the 145 subjects from the Grant-White school only).

data(HolzingerSwineford1939)

Format

A data frame with 301 observations of 15 variables.

id

Identifier

sex

Gender

ageyr

Age, year part

agemo

Age, month part

school

School (Pasteur or Grant-White)

grade

Grade

x1

Visual perception

x2

Cubes

x3

Lozenges

x4

Paragraph comprehension

x5

Sentence completion

x6

Word meaning

x7

Speeded addition

x8

Speeded counting of dots

x9

Speeded discrimination straight and curved capitals

Source

This dataset was originally retrieved from http://web.missouri.edu/~kolenikovs/stata/hs-cfa.dta (link no longer active) and converted to an R dataset.

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.

See also

cfa

Examples

head(HolzingerSwineford1939)
#>   id sex ageyr agemo  school grade       x1   x2    x3       x4   x5        x6
#> 1  1   1    13     1 Pasteur     7 3.333333 7.75 0.375 2.333333 5.75 1.2857143
#> 2  2   2    13     7 Pasteur     7 5.333333 5.25 2.125 1.666667 3.00 1.2857143
#> 3  3   2    13     1 Pasteur     7 4.500000 5.25 1.875 1.000000 1.75 0.4285714
#> 4  4   1    13     2 Pasteur     7 5.333333 7.75 3.000 2.666667 4.50 2.4285714
#> 5  5   2    12     2 Pasteur     7 4.833333 4.75 0.875 2.666667 4.00 2.5714286
#> 6  6   2    14     1 Pasteur     7 5.333333 5.00 2.250 1.000000 3.00 0.8571429
#>         x7   x8       x9
#> 1 3.391304 5.75 6.361111
#> 2 3.782609 6.25 7.916667
#> 3 3.260870 3.90 4.416667
#> 4 3.000000 5.30 4.861111
#> 5 3.695652 6.30 5.916667
#> 6 4.347826 6.65 7.500000