Yamaguchi87: Occupational Mobility in Three Countries

In vcdExtra: 'vcd' Extensions and Additions

Description

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 UpNM LoNM UpM LoM Farm

Father

a factor with levels UpNM LoNM UpM LoM Farm

Country

a factor with levels US UK Japan

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)
##

Example output

Loading required package: vcd
Loading required package: grid
Loading required package: gnm
               Son UpNM LoNM  UpM  LoM Farm
Father Country                             
UpNM   US          1275  364  274  272   17
       UK           474  129   87  124   11
       Japan        127  101   24   30   12
LoNM   US          1055  597  394  443   31
       UK           300  218  171  220    8
       Japan         86  207   64   61   13
UpM    US          1043  587 1045  951   47
       UK           438  254  669  703   16
       Japan         43   73  122   60   13
LoM    US          1159  791 1323 2046   52
       UK           601  388  932 1789   37
       Japan         35   51   62   66   11
Farm   US           666  496 1031 1632  646
       UK            76   56  125  295  191
       Japan        109  206  184  253  325
Analysis of Deviance Table

Model: poisson, link: log

Response: Freq

Terms added sequentially (first to last)


        Df Deviance Resid. Df Resid. Dev
NULL                       74      34313
Son      4   7034.4        70      27279
Father   4   3859.2        66      23419
Country  2  14231.1        64       9188
Analysis of Deviance Table

Model: poisson, link: log

Response: Freq

Terms added sequentially (first to last)


               Df Deviance Resid. Df Resid. Dev
NULL                              74      34313
Son             4   7034.4        70      27279
Father          4   3859.2        66      23419
Country         2  14231.1        64       9188
Son:Country     8   1062.9        56       8125
Father:Country  8   2533.8        48       5592
Analysis of Deviance Table

Model: poisson, link: log

Response: Freq

Terms added sequentially (first to last)


                          Df Deviance Resid. Df Resid. Dev
NULL                                         74      34313
Son                        4   7034.4        70      27279
Father                     4   3859.2        66      23419
Country                    2  14231.1        64       9188
Son:Country                8   1062.9        56       8125
Father:Country             8   2533.8        48       5592
Country:Diag(Son, Father) 15   4255.3        33       1336

vcdExtra documentation built on May 31, 2017, 4:57 a.m.