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.
Usage
data(Yamaguchi87)
Format
A frequency data frame with 75 observations on the following 4 variables. The total sample size is 28887.
Son
a factor with levels UpNMLoNMUpMLoMFarm
Father
a factor with levels UpNMLoNMUpMLoMFarm
Country
a factor with levels USUKJapan
Freq
a numeric vector
Details
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).
Source
Yamaguchi, K. (1987).
Models for comparing mobility tables: toward parsimony and substance,
American Sociological Review, vol. 52 (Aug.), 482-494, Table 1
References
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.
Examples
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)
##