Occupational Mobility in Three Countries
Yamaguchi (1987) presented this three-way frequency table, cross-classifying occupational categories of sons and fathers in the United States, United Kingdom and Japan. This data set has become a classic for models comparing two-way mobility tables across layers corresponding to countries, groups or time (e.g., Goodman and Hout, 1998; Xie, 1992).
The US data were derived from the 1973 OCG-II survey; those for the UK from the 1972 Oxford Social Mobility Survey; those for Japan came from the 1975 Social Stratification and Mobility survey. They pertain to men aged 20-64.
data(Yamaguchi87)
A frequency data frame with 75 observations on the following 4 variables. The total sample size is 28887.
Sona factor with levels UpNM LoNM UpM LoM Farm
Fathera factor with levels UpNM LoNM UpM LoM Farm
Countrya factor with levels US UK Japan
Freqa numeric vector
Five status categories – upper and lower
nonmanuals (UpNM, LoNM),
upper and lower manuals (UpM, LoM),
and Farm) are used for both fathers' occupations and
sons' occupations.
Upper nonmanuals are professionals, managers, and officials; lower nonmanuals are proprietors, sales workers, and clerical workers; upper manuals are skilled workers; lower manuals are semi-skilled and unskilled nonfarm workers; and farm workers are farmers and farm laborers.
Some of the models from Xie (1992), Table 1, are fit in demo(yamaguchi-xie).
Yamaguchi, K. (1987). Models for comparing mobility tables: toward parsimony and substance, American Sociological Review, vol. 52 (Aug.), 482-494, Table 1
Goodman, L. A. and Hout, M. (1998). Statistical Methods and Graphical Displays for Analyzing How the Association Between Two Qualitative Variables Differs Among Countries, Among Groups, Or Over Time: A Modified Regression-Type Approach. Sociological Methodology, 28 (1), 175-230.
Xie, Yu (1992). The log-multiplicative layer effect model for comparing mobility tables. American Sociological Review, 57 (June), 380-395.
data(Yamaguchi87)
# reproduce Table 1
structable(~ Father + Son + Country, Yamaguchi87)
# create table form
Yama.tab <- xtabs(Freq ~ Son + Father + Country, data=Yamaguchi87)
# define mosaic labeling_args for convenient reuse in 3-way displays
largs <- list(rot_labels=c(right=0), offset_varnames = c(right = 0.6),
offset_labels = c(right = 0.2),
set_varnames = c(Son="Son's status", Father="Father's status")
)
###################################
# Fit some models & display mosaics
# Mutual independence
yama.indep <- glm(Freq ~ Son + Father + Country, data=Yamaguchi87, family=poisson)
anova(yama.indep)
mosaic(yama.indep, ~Son+Father, main="[S][F] ignoring country")
mosaic(yama.indep, ~Country + Son + Father, condvars="Country",
labeling_args=largs,
main='[S][F][C] Mutual independence')
# no association between S and F given country ('perfect mobility')
# asserts same associations for all countries
yama.noRC <- glm(Freq ~ (Son + Father) * Country, data=Yamaguchi87, family=poisson)
anova(yama.noRC)
mosaic(yama.noRC, ~~Country + Son + Father, condvars="Country",
labeling_args=largs,
main="[SC][FC] No [SF] (perfect mobility)")
# ignore diagonal cells
yama.quasi <- update(yama.noRC, ~ . + Diag(Son,Father):Country)
anova(yama.quasi)
mosaic(yama.quasi, ~Son+Father, main="Quasi [S][F]")
## see also:
# demo(yamaguchi-xie)
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