galo

The objects (individuals) are 1290 school children in the sixth grade of elementary
school in the city of Groningen (Netherlands) in 1959.

datasets

Contains various functions for optimal scaling. One function performs optimal scaling by maximizing an aspect (i.e. a target function such as the sum of eigenvalues, sum of squared correlations, squared multiple correlations, etc.) of the corresponding correlation matrix. Another function performs implements the LINEALS approach for optimal scaling by minimization of an aspect based on pairwise correlations and correlation ratios. The resulting correlation matrix and category scores can be used for further multivariate methods such as structural equation models.

Patrick Mair

aspect

A General Framework for Multivariate Analysis with Optimal
Scaling

Jan De Leeuw

galo function

Data frame with the five variables Gender, IQ, Advice, SES (fathers occupation) and School. IQ (original range 60 to 144) 
has been categorized into 9 ordered categories and the schools are enumerated from 1 to 37.
SES: 
LoWC = Lower white collar; MidWC = Middle white collar; Prof = Professional, Managers;
Shop = Shopkeepers; Skil = Schooled labor; Unsk = Unskilled labor. 
Advice:
Agr = Agricultural; Ext = Extended primary education; Gen = General; 
Grls = Secondary school for girls; Man = Manual, including housekeeping; 
None = No further education; Uni = Pre-University.

galo: GALO dataset

Description

Usage

Arguments

Format

References

Examples