Pub Date : 2021-02-01Epub Date: 2020-12-08DOI: 10.1177/0081175020973054
Xi Song
Most social mobility studies take a two-generation perspective, in which intergenerational relationships are represented by the association between parents' and offspring's socioeconomic status. This approach, albeit widely adopted in the literature, has serious limitations when more than two generations of families are considered. In particular, it ignores the role of families' demographic behaviors in moderating mobility outcomes and the joint role of mobility and demography in shaping long-run family and population processes. This paper provides a demographic approach to the study of multigenerational social mobility, incorporating demographic mechanisms of births, deaths, and mating into statistical models of social mobility. Compared to previous mobility models for estimating the probability of offspring's mobility conditional on parent's social class, the proposed joint demography-mobility model treats the number of offspring in various social classes as the outcome of interest. This new approach shows the extent to which demographic processes may amplify or dampen the effects of family socioeconomic positions due to the direction and strength of the interaction between mobility and differentials in demographic behaviors. I illustrate various demographic methods for studying multigenerational mobility with empirical examples using the IPUMS linked historical U.S. census representative samples (1850 to 1930), the Panel Study of Income Dynamics (1968 to 2015), and simulation data that show other possible scenarios resulting from demography-mobility interactions.
{"title":"Multigenerational Social Mobility: A Demographic Approach.","authors":"Xi Song","doi":"10.1177/0081175020973054","DOIUrl":"https://doi.org/10.1177/0081175020973054","url":null,"abstract":"<p><p>Most social mobility studies take a two-generation perspective, in which intergenerational relationships are represented by the association between parents' and offspring's socioeconomic status. This approach, albeit widely adopted in the literature, has serious limitations when more than two generations of families are considered. In particular, it ignores the role of families' demographic behaviors in moderating mobility outcomes and the joint role of mobility and demography in shaping long-run family and population processes. This paper provides a demographic approach to the study of multigenerational social mobility, incorporating demographic mechanisms of births, deaths, and mating into statistical models of social mobility. Compared to previous mobility models for estimating the probability of offspring's mobility conditional on parent's social class, the proposed joint demography-mobility model treats the number of offspring in various social classes as the outcome of interest. This new approach shows the extent to which demographic processes may amplify or dampen the effects of family socioeconomic positions due to the direction and strength of the interaction between mobility and differentials in demographic behaviors. I illustrate various demographic methods for studying multigenerational mobility with empirical examples using the IPUMS linked historical U.S. census representative samples (1850 to 1930), the Panel Study of Income Dynamics (1968 to 2015), and simulation data that show other possible scenarios resulting from demography-mobility interactions.</p>","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"51 1","pages":"1-43"},"PeriodicalIF":3.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020973054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39218980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-11DOI: 10.1177/0081175020982632
S. Johfre, J. Freese
Social scientists often present modeling results from categorical explanatory variables, such as gender, race, and marital status, as coefficients representing contrasts to a “reference” group. Although choosing the reference category may seem arbitrary, the authors argue that it is an intrinsically meaningful act that affects the interpretability of results. Reference category selection foregrounds some contrasts over others. Also, selecting a culturally dominant group as the reference can subtly reify the notion that dominant groups are the most “normal.” The authors find that three of four recently published tables in Demography and American Sociological Review that include race or gender explanatory variables use dominant groups (i.e., male or white) as the reference group. Furthermore, the tables rarely state what the reference is: only half of tables with race variables and one-fifth of tables with gender variables explicitly specify the reference category; the rest leave it up to the reader to check the methods section or simply guess. As an alternative to this apparently standard practice, the authors suggest guidelines for intentionally and responsibly choosing a reference category. The authors then discuss alternative ways to convey results from categorical explanatory variables that avoid the problems of reference categories entirely.
{"title":"Reconsidering the Reference Category","authors":"S. Johfre, J. Freese","doi":"10.1177/0081175020982632","DOIUrl":"https://doi.org/10.1177/0081175020982632","url":null,"abstract":"Social scientists often present modeling results from categorical explanatory variables, such as gender, race, and marital status, as coefficients representing contrasts to a “reference” group. Although choosing the reference category may seem arbitrary, the authors argue that it is an intrinsically meaningful act that affects the interpretability of results. Reference category selection foregrounds some contrasts over others. Also, selecting a culturally dominant group as the reference can subtly reify the notion that dominant groups are the most “normal.” The authors find that three of four recently published tables in Demography and American Sociological Review that include race or gender explanatory variables use dominant groups (i.e., male or white) as the reference group. Furthermore, the tables rarely state what the reference is: only half of tables with race variables and one-fifth of tables with gender variables explicitly specify the reference category; the rest leave it up to the reader to check the methods section or simply guess. As an alternative to this apparently standard practice, the authors suggest guidelines for intentionally and responsibly choosing a reference category. The authors then discuss alternative ways to convey results from categorical explanatory variables that avoid the problems of reference categories entirely.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"51 1","pages":"253 - 269"},"PeriodicalIF":3.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020982632","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47070015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-06DOI: 10.1177/0081175020981120
K. Yamaguchi
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.
{"title":"Multigroup Segregation Analyses with Covariates","authors":"K. Yamaguchi","doi":"10.1177/0081175020981120","DOIUrl":"https://doi.org/10.1177/0081175020981120","url":null,"abstract":"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.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"51 1","pages":"224 - 252"},"PeriodicalIF":3.0,"publicationDate":"2021-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020981120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48735653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-05DOI: 10.1177/0081175020959401
T. Liao, A. Fasang
How can we statistically assess differences in groups of life-course trajectories? The authors address a long-standing inadequacy of social sequence analysis by proposing an adaption of the Bayesian information criterion (BIC) and the likelihood-ratio test (LRT) for assessing differences in groups of sequence data. Unlike previous methods, this adaption provides a useful measure for degrees of difference, that is, the substantive significance, and the statistical significance of differences between predefined groups of life-course trajectories. The authors present a simulation study and an empirical application on whether employment life-courses converged after reunification in the former East Germany and West Germany, using data for six birth-cohort groups ages 15 to 40 years from the German National Education Panel Study. The new methods allow the authors to show that convergence of employment life-courses around reunification was stronger for men than for women and that it was most pronounced in terms of the duration of employment states but weaker for their order and timing in the life-course. Convergence of East German and West German women’s employment lives set in earlier and reflects a secular trend toward a more gender-egalitarian division of labor in West Germany that is unrelated to reunification. The simulation study and the substantive application demonstrate the usefulness of the proposed BIC and LRT methods for assessing group differences in sequence data.
{"title":"Comparing Groups of Life-Course Sequences Using the Bayesian Information Criterion and the Likelihood-Ratio Test","authors":"T. Liao, A. Fasang","doi":"10.1177/0081175020959401","DOIUrl":"https://doi.org/10.1177/0081175020959401","url":null,"abstract":"How can we statistically assess differences in groups of life-course trajectories? The authors address a long-standing inadequacy of social sequence analysis by proposing an adaption of the Bayesian information criterion (BIC) and the likelihood-ratio test (LRT) for assessing differences in groups of sequence data. Unlike previous methods, this adaption provides a useful measure for degrees of difference, that is, the substantive significance, and the statistical significance of differences between predefined groups of life-course trajectories. The authors present a simulation study and an empirical application on whether employment life-courses converged after reunification in the former East Germany and West Germany, using data for six birth-cohort groups ages 15 to 40 years from the German National Education Panel Study. The new methods allow the authors to show that convergence of employment life-courses around reunification was stronger for men than for women and that it was most pronounced in terms of the duration of employment states but weaker for their order and timing in the life-course. Convergence of East German and West German women’s employment lives set in earlier and reflects a secular trend toward a more gender-egalitarian division of labor in West Germany that is unrelated to reunification. The simulation study and the substantive application demonstrate the usefulness of the proposed BIC and LRT methods for assessing group differences in sequence data.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"51 1","pages":"44 - 85"},"PeriodicalIF":3.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020959401","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45498005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1177/0081175020955216
David Willer, Pamela Emanuelson
Many refinements of statistical design have been offered to solve the replication problem identified by the Open Science Collaboration and Camerer and colleagues. There are, however, two distinct kinds of experimentation: Fisher design and theory designed. Therefore, there are two kinds of replication. Only for the Fisher design does replication reproduce conditions of prior experiments in order to compare new with prior results, and only there has a replication problem been demonstrated. In contrast, replications for theory-designed experiments test experimental results against theoretical predictions, and only for theory-designed experiments can replication be extended broadly across the scope of a theory. The authors analyze the logic of the two types of experiments as well as hybrids that mix qualities of both.
{"title":"Theory and the Replication Problem","authors":"David Willer, Pamela Emanuelson","doi":"10.1177/0081175020955216","DOIUrl":"https://doi.org/10.1177/0081175020955216","url":null,"abstract":"Many refinements of statistical design have been offered to solve the replication problem identified by the Open Science Collaboration and Camerer and colleagues. There are, however, two distinct kinds of experimentation: Fisher design and theory designed. Therefore, there are two kinds of replication. Only for the Fisher design does replication reproduce conditions of prior experiments in order to compare new with prior results, and only there has a replication problem been demonstrated. In contrast, replications for theory-designed experiments test experimental results against theoretical predictions, and only for theory-designed experiments can replication be extended broadly across the scope of a theory. The authors analyze the logic of the two types of experiments as well as hybrids that mix qualities of both.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"51 1","pages":"146 - 165"},"PeriodicalIF":3.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020955216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48257035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-29DOI: 10.1177/00811750221145166
Marion Hoffman, Per Block, T. Snijders
Despite the central role of self-assembled groups in animal and human societies, statistical tools to explain their composition are limited. The authors introduce a statistical framework for cross-sectional observations of groups with exclusive membership to illuminate the social and organizational mechanisms that bring people together. Drawing from stochastic models for networks and partitions, the proposed framework introduces an exponential family of distributions for partitions. The authors derive its main mathematical properties and suggest strategies to specify and estimate such models. A case study on hackathon events applies the developed framework to the study of mechanisms underlying the formation of self-assembled project teams.
{"title":"Modeling Partitions of Individuals","authors":"Marion Hoffman, Per Block, T. Snijders","doi":"10.1177/00811750221145166","DOIUrl":"https://doi.org/10.1177/00811750221145166","url":null,"abstract":"Despite the central role of self-assembled groups in animal and human societies, statistical tools to explain their composition are limited. The authors introduce a statistical framework for cross-sectional observations of groups with exclusive membership to illuminate the social and organizational mechanisms that bring people together. Drawing from stochastic models for networks and partitions, the proposed framework introduces an exponential family of distributions for partitions. The authors derive its main mathematical properties and suggest strategies to specify and estimate such models. A case study on hackathon events applies the developed framework to the study of mechanisms underlying the formation of self-assembled project teams.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"53 1","pages":"1 - 41"},"PeriodicalIF":3.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43482772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-03DOI: 10.1177/00811750221108086
Molly M. King
Researchers often need to work with categorical income data. The typical nonparametric (including midpoint) and parametric estimation methods used to estimate summary statistics both have advantages, but they carry assumptions that cause them to deviate in important ways from real-world income distributions. The method introduced here, random empirical distribution imputation (REDI), imputes discrete observations using binned income data, while also calculating summary statistics. REDI achieves this through random cold-deck imputation from a real-world reference data set (demonstrated here using the Current Population Survey Annual Social and Economic Supplement). This method can be used to reconcile bins between data sets or across years and handle top incomes. REDI has other advantages for computing values of an income distribution that is nonparametric, bin consistent, area and variance preserving, continuous, and computationally fast. The author provides proof of concept using two years of the American Community Survey. The method is available as the redi command for Stata.
{"title":"REDI for Binned Data: A Random Empirical Distribution Imputation Method for Estimating Continuous Incomes","authors":"Molly M. King","doi":"10.1177/00811750221108086","DOIUrl":"https://doi.org/10.1177/00811750221108086","url":null,"abstract":"Researchers often need to work with categorical income data. The typical nonparametric (including midpoint) and parametric estimation methods used to estimate summary statistics both have advantages, but they carry assumptions that cause them to deviate in important ways from real-world income distributions. The method introduced here, random empirical distribution imputation (REDI), imputes discrete observations using binned income data, while also calculating summary statistics. REDI achieves this through random cold-deck imputation from a real-world reference data set (demonstrated here using the Current Population Survey Annual Social and Economic Supplement). This method can be used to reconcile bins between data sets or across years and handle top incomes. REDI has other advantages for computing values of an income distribution that is nonparametric, bin consistent, area and variance preserving, continuous, and computationally fast. The author provides proof of concept using two years of the American Community Survey. The method is available as the redi command for Stata.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"52 1","pages":"220 - 253"},"PeriodicalIF":3.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43903799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01Epub Date: 2020-02-11DOI: 10.1177/0081175020903348
Liying Luo, James S Hodges
Random effects (RE) models have been widely used to study the contextual effects of structures such as neighborhood or school. The RE approach has recently been applied to age-period-cohort (APC) models that are unidentified because the predictors are exactly linearly dependent. However, it has not been fully understood how the RE specification identifies these otherwise unidentified APC models. We address this challenge by first making explicit that RE-APC models have greater-not less-rank deficiency than the traditional fixed-effects model, followed by two empirical examples. We then provide intuition and a mathematical proof to explain that for APC models with one RE, treating one effect as an RE is equivalent to constraining the estimates of that effect's linear component and the random intercept to be zero. For APC models with two RE's, the effective constraints implied by the model depend on the true (i.e., in the data-generating mechanism) non-linear components of the effects that are modeled as RE's, so that the estimated linear components of the RE's are determined by the true non-linear components of those effects. In conclusion, RE-APC models impose arbitrary though highly obscure constraints and thus do not differ qualitatively from other constrained APC estimators.
随机效应（RE）模型已被广泛用于研究邻里或学校等结构的环境效应。最近，随机效应方法被应用于年龄-时期-队列（APC）模型，这些模型由于预测因子完全线性相关而无法识别。然而，人们还没有完全理解 RE 规范是如何识别这些原本无法识别的 APC 模型的。为了应对这一挑战，我们首先明确指出，与传统的固定效应模型相比，RE-APC 模型的秩缺陷更大，而不是更小。然后，我们提供了直觉和数学证明，解释了对于有一个 RE 的 APC 模型，将一个效应视为 RE 等于限制该效应的线性分量和随机截距的估计值为零。对于有两个 RE 的 APC 模型，模型隐含的有效约束取决于被作为 RE 的效应的真实（即在数据生成机制中）非线性成分，因此 RE 的估计线性成分由这些效应的真实非线性成分决定。总之，RE-APC 模型施加了任意的但非常不明显的约束，因此与其他受约束的 APC 估计模型没有本质区别。
{"title":"Constraints in Random Effects Age-Period-Cohort Models.","authors":"Liying Luo, James S Hodges","doi":"10.1177/0081175020903348","DOIUrl":"10.1177/0081175020903348","url":null,"abstract":"<p><p>Random effects (RE) models have been widely used to study the contextual effects of structures such as neighborhood or school. The RE approach has recently been applied to age-period-cohort (APC) models that are unidentified because the predictors are exactly linearly dependent. However, it has not been fully understood how the RE specification identifies these otherwise unidentified APC models. We address this challenge by first making explicit that RE-APC models have greater-not less-rank deficiency than the traditional fixed-effects model, followed by two empirical examples. We then provide intuition and a mathematical proof to explain that for APC models with one RE, treating one effect as an RE is equivalent to constraining the estimates of that effect's linear component and the random intercept to be zero. For APC models with two RE's, the effective constraints implied by the model depend on the true (i.e., in the data-generating mechanism) non-linear components of the effects that are modeled as RE's, so that the estimated <i>linear</i> components of the RE's are determined by the true <i>non-linear</i> components of those effects. In conclusion, RE-APC models impose arbitrary though highly obscure constraints and thus do not differ qualitatively from other constrained APC estimators.</p>","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"50 1","pages":"276-317"},"PeriodicalIF":2.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838118/pdf/nihms-1849300.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10541044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-21DOI: 10.1177/0081175020937028
Pablo A. Mitnik, D. Grusky
{"title":"A Forced Critique of the Intergenerational Elasticity of the Conditional Expectation","authors":"Pablo A. Mitnik, D. Grusky","doi":"10.1177/0081175020937028","DOIUrl":"https://doi.org/10.1177/0081175020937028","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"50 1","pages":"112 - 130"},"PeriodicalIF":3.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175020937028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48879489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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