vcdExtra (version 0.7-1)

Glass: British Social Mobility from Glass(1954)

Description

Glass(1954) gave this 5 x 5 table on the occupations of 3500 British fathers and their sons.

Usage

data("Glass")

Format

A frequency data frame with 25 observations on the following 3 variables representing a 5 x 5 table with 3500 cases.

father

a factor with levels Managerial Professional Skilled Supervisory Unskilled

son

a factor with levels Managerial Professional Skilled Supervisory Unskilled

Freq

a numeric vector

Details

The occupational categories in order of status are: (1) Professional \& High Administrative (2) Managerial, Executive \& High Supervisory (3) Low Inspectional \& Supervisory (4) Routine Nonmanual \& Skilled Manual (5) Semi- \& Unskilled Manual

However, to make the point that factors are ordered alphabetically by default, Friendly \& Meyer (2016) introduce this data set in the form given here.

References

Bishop, Y. M. M. and Fienberg, S. E. and Holland, P. W. (1975). Discrete Multivariate Analysis: Theory and Practice, MIT Press.

Friendly, M. and Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: Chapman & Hall/CRC. http://ddar.datavis.ca.

Examples

# NOT RUN {
data(Glass)
glass.tab <- xtabs(Freq ~ father + son, data=Glass)

largs <- list(set_varnames=list(father="Father's Occupation", son="Son's Occupation"),
              abbreviate=10)
gargs <- list(interpolate=c(1,2,4,8))
mosaic(glass.tab, shade=TRUE, labeling_args=largs, gp_args=gargs,
  main="Alphabetic order", legend=FALSE, rot_labels=c(20,90,0,70))

# reorder by status
ord <- c(2, 1, 4, 3, 5) 
mosaic(glass.tab[ord, ord], shade=TRUE, labeling_args=largs,  gp_args=gargs,
  main="Effect order", legend=FALSE, rot_labels=c(20,90,0,70))

# }