Yamaguchi87(vcdExtra)
Yamaguchi87()所属R语言包：vcdExtra
Occupational Mobility in Three Countries
在三个国家的职业流动
译者：生物统计家园网 机器人LoveR
描述----------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).
山口（1987）提出了这三个方法，频率表，跨职业类别分类的儿子和父亲在美国，英国和日本。该数据集已成为经典之作比较的型号对应的国家，团体或时间（例如，古德曼和豪特，1998年，谢，1992），跨层的双向流动表。
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.
OCG-II从1973年的调查数据来源于美国，英国从1972年的牛津大学社会流动调查，日本从1975年的社会分层与流动调查。它们涉及到男性年龄20-64。
用法----------Usage----------
data(Yamaguchi87)
格式----------Format----------
A frequency data frame with 75 observations on the following 4 variables. The total sample size is 28887.
一种频率的数据框与75上的以下4个变量的观察。总样本数为28887。
Son a factor with levels UpNM LoNM UpM LoM Farm
Son的一个因素水平UpNMLoNMUpMLoMFarm
Father a factor with levels UpNM LoNM UpM LoM Farm
Father的一个因素水平UpNMLoNMUpMLoMFarm
Country a factor with levels US UK Japan
Country的一个因素水平USUKJapan
Freq a numeric vector
Freq一个数值向量
Details
详细信息----------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.
五种状态 - 上下nonmanuals（UpNM，LoNM），上下手册（UpM，LoM），和Farm）是用来两个父亲的职业和儿子的职业。
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.
上nonmanuals是专业人士，经理和政府官员，低nonmanuals的所有人，销售人员，文员，上手册的技术工人;较低的手册是半熟练和非熟练非农工人和农场工人，农民和雇农。
Some of the models from Xie (1992), Table 1, are fit in demo(yamaguchi-xie).
有些谢（1992），见表1的模型，适合在demo(yamaguchi-xie)。
源----------Source----------
Yamaguchi, K. (1987). Models for comparing mobility tables: toward parsimony and substance, American Sociological Review, vol. 52 (Aug.), 482-494, Table 1
山口，K.（1987）。模型比较流动表对简约和物质的，美国社会学评论，第一卷。 52（8月），482-494，表1
参考文献----------References----------
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.
The log-multiplicative layer effect model for comparing mobility tables. American Sociological Review, 57 (June), 380-395.
实例----------Examples----------
data(Yamaguchi87)
# reproduce Table 1[再现表1]
structable(~ Father + Son + Country, Yamaguchi87)
# create table form[创建表格的形式]
Yama.tab <- xtabs(Freq ~ Son + Father + Country, data=Yamaguchi87)
# define mosaic labeling_args for convenient reuse in 3-way displays[在3路显示定义马赛克labeling_args方便再用]
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[适合一些模型显示马赛克]
# Mutual independence[相互独立]
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')[S和F特定国家之间没有关联（“完美的流动性”）]
# asserts same associations for all countries[断言同一协会的所有国家]
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[忽略对角线单元的]
yama.quasi <- update(yama.noRC, ~ . + Diag(Son,Father):Country)
anova(yama.quasi)
mosaic(yama.quasi, ~Son+Father, main="Quasi [S][F]")
## see also:[＃另参考：]
# demo(yamaguchi-xie)[演示（山口谢）]
##[＃]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-10-1 14:45:21
