The author introduces methods for the decomposition analysis of multigroup segregation measured by the index of dissimilarity, the squared coefficient of variation, and Theil’s entropy measure. Using a new causal framework, the author takes a unified approach to the decomposition analysis by specifying conditions that must be satisfied to decompose segregation into unexplained and explained components. Here, the unexplained component represents the direct effects of the group variable on the conditional probability of acquiring a social position—such as a residential district in an analysis of residential segregation or an occupation in an analysis of occupational segregation—and the explained component represents indirect effects of the group variable on the outcome through covariates. The major merit of this approach is its ability to control individual-level covariates for the decomposition analysis of segregation. Two methods, one for semiparametric outcome models with the identity link function and the other for semiparametric outcome models with the multinomial logit link function, are introduced in this unified framework. The application of these methods focuses on occupational segregation among racial/ethnic groups. Father’s occupation, subject’s educational attainment, and the region of interview are included as covariates, using data from the General Social Surveys.

作者介绍了通过相异指数，变异系数平方和Theil熵测度测得的多族偏析的分解方法。通过使用新的因果框架，作者通过指定必须满足的条件才能将分解分解为无法解释和解释的组件，从而采用统一的方法进行分解分析。在这里，无法解释的部分代表群体变量对获得社会地位的条件概率的直接影响（例如，在分析居住隔离的过程中是居住区，在分析职业隔离的情况中是职业），而所解释的部分则代表间接影响。组变量通过协变量对结果的影响。这种方法的主要优点是它能够控制个人级别的协变量，以进行分离的分解分析。在此统一框架中介绍了两种方法，一种用于具有标识链接功能的半参数结果模型，另一种用于具有多项式logit链接功能的半参数结果模型。这些方法的应用着重于种族/族裔群体之间的职业隔离。父亲的职业，受教育者的学历和面试地区作为协变量，使用了来自《综合社会调查》的数据。在此统一框架中介绍。这些方法的应用着重于种族/族裔群体之间的职业隔离。父亲的职业，受教育者的学历以及面试的区域都作为协变量包括在内，使用的是“一般社会调查”中的数据。在此统一框架中介绍。这些方法的应用着重于种族/族裔群体之间的职业隔离。父亲的职业，受教育者的学历和面试地区作为协变量，使用了来自《综合社会调查》的数据。