Pub Date : 2024-07-25DOI: 10.1177/00811750241265336
Bolun Zhang, Yimang Zhou, Dai Li
Validation is at the heart of methodological discussions about topic modeling. The authors argue that validation based on human reading hinges on distinctive words and readers’ labeling of a topic, and it overlooks the probability of conflicting results from semantically similar models, such as regressions or other methods. This runs counter to the presumption that topic modeling can reveal features of documents that have some measurable association with social aspects outside the text. The authors develop a similar topic identifying procedure to verify that semantically similar solutions yield similar results in further analysis. The authors argue that future validations of topic modeling must consider such procedures.
{"title":"Can Human Reading Validate a Topic Model?","authors":"Bolun Zhang, Yimang Zhou, Dai Li","doi":"10.1177/00811750241265336","DOIUrl":"https://doi.org/10.1177/00811750241265336","url":null,"abstract":"Validation is at the heart of methodological discussions about topic modeling. The authors argue that validation based on human reading hinges on distinctive words and readers’ labeling of a topic, and it overlooks the probability of conflicting results from semantically similar models, such as regressions or other methods. This runs counter to the presumption that topic modeling can reveal features of documents that have some measurable association with social aspects outside the text. The authors develop a similar topic identifying procedure to verify that semantically similar solutions yield similar results in further analysis. The authors argue that future validations of topic modeling must consider such procedures.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774347","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 : 2024-07-25DOI: 10.1177/00811750241260731
Siwei Cheng, Andrew Levine, Ananda Martin-Caughey
In addition to overall dispersion, the distributional shape of economic status has attracted growing attention in the inequality literature. Economic polarization is a specific form of distributional change, characterized by a shrinking middle of the distribution and a growing top and bottom, with potentially important and unique social consequences. Building on relative distribution methods and drawing from the literature on job polarization, the authors develop an approach for analyzing economic polarization at the individual level. The method has three useful features. First, it offers intuitive and flexible measurement of economic polarization both between and within categories. Second, it helps disentangle two potential sources of economic polarization: compositional change, which involves changes to the allocation of workers across categories, and relative economic status change, which involves changes to the allocation of economic rewards between individuals. Third, it enables researchers to uncover and examine potential heterogeneity in economic polarization, for example, across occupations, geographic units, demographic and educational groups, and firms. The authors demonstrate the utility of this approach through two empirical applications: (1) an analysis of trends in wage polarization between and within occupations and (2) an examination of geographic variation in income polarization.
{"title":"Using Relative Distribution Methods to Study Economic Polarization across Categories and Contexts","authors":"Siwei Cheng, Andrew Levine, Ananda Martin-Caughey","doi":"10.1177/00811750241260731","DOIUrl":"https://doi.org/10.1177/00811750241260731","url":null,"abstract":"In addition to overall dispersion, the distributional shape of economic status has attracted growing attention in the inequality literature. Economic polarization is a specific form of distributional change, characterized by a shrinking middle of the distribution and a growing top and bottom, with potentially important and unique social consequences. Building on relative distribution methods and drawing from the literature on job polarization, the authors develop an approach for analyzing economic polarization at the individual level. The method has three useful features. First, it offers intuitive and flexible measurement of economic polarization both between and within categories. Second, it helps disentangle two potential sources of economic polarization: compositional change, which involves changes to the allocation of workers across categories, and relative economic status change, which involves changes to the allocation of economic rewards between individuals. Third, it enables researchers to uncover and examine potential heterogeneity in economic polarization, for example, across occupations, geographic units, demographic and educational groups, and firms. The authors demonstrate the utility of this approach through two empirical applications: (1) an analysis of trends in wage polarization between and within occupations and (2) an examination of geographic variation in income polarization.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774327","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 : 2024-07-25DOI: 10.1177/00811750241260729
Moeen Mostafavi, Michael D. Porter, Dawn T. Robinson
The authors introduce BERTNN (Bidirectional Encoder Representations from Transformers Neural Network), a novel methodology designed to expand affective lexicons, a critical component in sociological research. BERTNN estimates the affective meanings and their distribution for new concepts, bypassing the need for extensive surveys by leveraging their contextual usage in language. The cornerstone of BERTNN is the use of nuanced word embeddings from Bidirectional Encoder Representations from Transformers. BERTNN uniquely encodes words within the framework of synthesized social event sentences, preserving their meaning across actor-behavior-object positions. The model is fine-tuned on the basis of the implied sentiment changes, providing a more refined estimation of affective meanings. BERTNN outperforms previous approaches, setting a new standard in deriving multidimensional affective meanings for novel concepts. It efficiently replicates sentiment ratings that traditionally require extensive survey hours, demonstrating the power of automated modeling in sociological research. The expanded affective lexicons that can be produced with BERTNN cater to shifting cultural meanings and diverse subgroups, demonstrating the potential of computational linguistics to enrich the measurement tools in sociological research. This article underscores the novelty and significance of BERTNN in the broader context of sociological methodology.
{"title":"Contextual Embeddings in Sociological Research: Expanding the Analysis of Sentiment and Social Dynamics","authors":"Moeen Mostafavi, Michael D. Porter, Dawn T. Robinson","doi":"10.1177/00811750241260729","DOIUrl":"https://doi.org/10.1177/00811750241260729","url":null,"abstract":"The authors introduce BERTNN (Bidirectional Encoder Representations from Transformers Neural Network), a novel methodology designed to expand affective lexicons, a critical component in sociological research. BERTNN estimates the affective meanings and their distribution for new concepts, bypassing the need for extensive surveys by leveraging their contextual usage in language. The cornerstone of BERTNN is the use of nuanced word embeddings from Bidirectional Encoder Representations from Transformers. BERTNN uniquely encodes words within the framework of synthesized social event sentences, preserving their meaning across actor-behavior-object positions. The model is fine-tuned on the basis of the implied sentiment changes, providing a more refined estimation of affective meanings. BERTNN outperforms previous approaches, setting a new standard in deriving multidimensional affective meanings for novel concepts. It efficiently replicates sentiment ratings that traditionally require extensive survey hours, demonstrating the power of automated modeling in sociological research. The expanded affective lexicons that can be produced with BERTNN cater to shifting cultural meanings and diverse subgroups, demonstrating the potential of computational linguistics to enrich the measurement tools in sociological research. This article underscores the novelty and significance of BERTNN in the broader context of sociological methodology.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774322","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 : 2024-05-28DOI: 10.1177/00811750241254363
Zsófia Papp, Pál Susánszky, Andrea Szabó
This study examines question-order effects in measuring satisfaction with democracy (SWD). Particularly, the authors are interested in whether the relative position of the question regarding satisfaction with the state of the economy (SWE) in the questionnaire affects responses to the SWD item. The authors conducted three independent split-ballot experiments in Hungary between March 2021 and May 2022. They report a significant and substantial negative priming effect that possibly leads to a systematic underestimation of SWD. Importantly, the authors find no question-order effect in the measurement of SWE. The analysis further reveals a contrast effect: when the SWD question is primed, the difference between SWE and SWD means increases. The authors’ final recommendation is that researchers either put the SWD question before the SWE item to avoid question-order bias or randomize question order. These findings should assist future data collection efforts (comparative or single-country studies) in developing and integrating a battery of satisfaction items into questionnaires and help users assess data quality.
{"title":"Question-Order Effect in the Study of Satisfaction with Democracy: Lessons from Three Split-Ballot Experiments","authors":"Zsófia Papp, Pál Susánszky, Andrea Szabó","doi":"10.1177/00811750241254363","DOIUrl":"https://doi.org/10.1177/00811750241254363","url":null,"abstract":"This study examines question-order effects in measuring satisfaction with democracy (SWD). Particularly, the authors are interested in whether the relative position of the question regarding satisfaction with the state of the economy (SWE) in the questionnaire affects responses to the SWD item. The authors conducted three independent split-ballot experiments in Hungary between March 2021 and May 2022. They report a significant and substantial negative priming effect that possibly leads to a systematic underestimation of SWD. Importantly, the authors find no question-order effect in the measurement of SWE. The analysis further reveals a contrast effect: when the SWD question is primed, the difference between SWE and SWD means increases. The authors’ final recommendation is that researchers either put the SWD question before the SWE item to avoid question-order bias or randomize question order. These findings should assist future data collection efforts (comparative or single-country studies) in developing and integrating a battery of satisfaction items into questionnaires and help users assess data quality.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171538","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 : 2024-04-15DOI: 10.1177/00811750241242791
Jessica P. Kunke, Ian Laga, Xiaoyue Niu, Tyler H. McCormick
The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps involves taking either an average of ratios or a ratio of averages. Using the ratio of averages for each step has so far been the most common approach. However, the authors present theoretical arguments that using the average of ratios at the second, prevalence-estimation step often has lower mean squared error when the random mixing assumption is violated, which seems likely in practice; this estimator was proposed early in NSUM development but has largely been unexplored and unused. Simulation results using an example network data set also support these findings. On the basis of this theoretical and empirical evidence, the authors suggest that future surveys that use a simple estimator may want to use this mixed estimator, and estimation methods based on this estimator may produce new improvements.
{"title":"Comparing the Robustness of Simple Network Scale-Up Method Estimators","authors":"Jessica P. Kunke, Ian Laga, Xiaoyue Niu, Tyler H. McCormick","doi":"10.1177/00811750241242791","DOIUrl":"https://doi.org/10.1177/00811750241242791","url":null,"abstract":"The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents’ degrees and estimating the prevalence of the hard-to-reach population of interest using respondents’ estimated degrees and the number of people they report knowing in the hard-to-reach group. Each of these two steps involves taking either an average of ratios or a ratio of averages. Using the ratio of averages for each step has so far been the most common approach. However, the authors present theoretical arguments that using the average of ratios at the second, prevalence-estimation step often has lower mean squared error when the random mixing assumption is violated, which seems likely in practice; this estimator was proposed early in NSUM development but has largely been unexplored and unused. Simulation results using an example network data set also support these findings. On the basis of this theoretical and empirical evidence, the authors suggest that future surveys that use a simple estimator may want to use this mixed estimator, and estimation methods based on this estimator may produce new improvements.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140588665","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 : 2024-04-12DOI: 10.1177/00811750241239049
Kazuo Yamaguchi, Jesse Zhou
The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The authors formulate the covariate effects to represent unique effects on each dependent variable so that they become independent across different dependent variables. The application focuses on the multiplicity of occupational attainments by analyzing how gender, race, educational attainment, and parental occupation characteristics affect three distinct but nonindependent dimensions of occupations: socioeconomic status, social skill level, and math and science skill levels.
{"title":"Multivariate Multinomial Logit Models with Associations among Dependent Variables","authors":"Kazuo Yamaguchi, Jesse Zhou","doi":"10.1177/00811750241239049","DOIUrl":"https://doi.org/10.1177/00811750241239049","url":null,"abstract":"The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The authors formulate the covariate effects to represent unique effects on each dependent variable so that they become independent across different dependent variables. The application focuses on the multiplicity of occupational attainments by analyzing how gender, race, educational attainment, and parental occupation characteristics affect three distinct but nonindependent dimensions of occupations: socioeconomic status, social skill level, and math and science skill levels.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140588551","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 : 2024-03-21DOI: 10.1177/00811750241236482
Callie H. Burt
Polygenic indices (PGI)—the new recommended label for polygenic scores in social science applications—are genetic summary scales often used to represent an individual’s liability for a disease, trait, or behavior on the basis of the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science data sets have facilitated increased uptake of PGIs in social science research, a trend that will likely continue. Yet most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, I provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. I summarize recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. I conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.
{"title":"Polygenic Indices (aka Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation","authors":"Callie H. Burt","doi":"10.1177/00811750241236482","DOIUrl":"https://doi.org/10.1177/00811750241236482","url":null,"abstract":"Polygenic indices (PGI)—the new recommended label for polygenic scores in social science applications—are genetic summary scales often used to represent an individual’s liability for a disease, trait, or behavior on the basis of the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science data sets have facilitated increased uptake of PGIs in social science research, a trend that will likely continue. Yet most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, I provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. I summarize recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. I conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140221973","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 : 2024-02-12DOI: 10.1177/00811750241228597
Inge Kryger Pedersen, Anders Blok
The authors argue that hitherto separate methodological conversations about abduction and comparison can be fruitfully brought together to generate novel, well-founded insights and retheorize an object of study in multiple-case qualitative inquiry. The authors call this abductive cross-case comparison and illustrate it by way of a collective study of how professional boundary work is changing under transnational conditions. In this study, the authors faced a common challenge in qualitative-comparative research: what to do when initial observations generate “surprises” that seem to confound the theoretical frameworks undergirding the comparison? To discuss how abductive inferences supported the authors’ response to this challenge, they explicate the acts of discovery and (re)conceptualization involved through various steps in a team-based research process. Building on the existing qualitative comparison literature, the authors suggest that such procedures fill a methodological gap and may hold great promise for overcoming obstacles in designing and implementing comparative research. Overall, the authors explicate and illustrate the method of abductive cross-case comparison, including their work as a research team. The aim of this article is thus to help sociologists implement better qualitative research that leverages a fuller potential of comparative designs to push beyond established knowledge and frameworks.
{"title":"Abductive Cross-Case Comparison in Qualitative Research: Methodological Lessons from the Teamwork Study of Professional Change","authors":"Inge Kryger Pedersen, Anders Blok","doi":"10.1177/00811750241228597","DOIUrl":"https://doi.org/10.1177/00811750241228597","url":null,"abstract":"The authors argue that hitherto separate methodological conversations about abduction and comparison can be fruitfully brought together to generate novel, well-founded insights and retheorize an object of study in multiple-case qualitative inquiry. The authors call this abductive cross-case comparison and illustrate it by way of a collective study of how professional boundary work is changing under transnational conditions. In this study, the authors faced a common challenge in qualitative-comparative research: what to do when initial observations generate “surprises” that seem to confound the theoretical frameworks undergirding the comparison? To discuss how abductive inferences supported the authors’ response to this challenge, they explicate the acts of discovery and (re)conceptualization involved through various steps in a team-based research process. Building on the existing qualitative comparison literature, the authors suggest that such procedures fill a methodological gap and may hold great promise for overcoming obstacles in designing and implementing comparative research. Overall, the authors explicate and illustrate the method of abductive cross-case comparison, including their work as a research team. The aim of this article is thus to help sociologists implement better qualitative research that leverages a fuller potential of comparative designs to push beyond established knowledge and frameworks.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782368","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 : 2024-02-12DOI: 10.1177/00811750241228597
Inge Kryger Pedersen, Anders Blok
The authors argue that hitherto separate methodological conversations about abduction and comparison can be fruitfully brought together to generate novel, well-founded insights and retheorize an object of study in multiple-case qualitative inquiry. The authors call this abductive cross-case comparison and illustrate it by way of a collective study of how professional boundary work is changing under transnational conditions. In this study, the authors faced a common challenge in qualitative-comparative research: what to do when initial observations generate “surprises” that seem to confound the theoretical frameworks undergirding the comparison? To discuss how abductive inferences supported the authors’ response to this challenge, they explicate the acts of discovery and (re)conceptualization involved through various steps in a team-based research process. Building on the existing qualitative comparison literature, the authors suggest that such procedures fill a methodological gap and may hold great promise for overcoming obstacles in designing and implementing comparative research. Overall, the authors explicate and illustrate the method of abductive cross-case comparison, including their work as a research team. The aim of this article is thus to help sociologists implement better qualitative research that leverages a fuller potential of comparative designs to push beyond established knowledge and frameworks.
{"title":"Abductive Cross-Case Comparison in Qualitative Research: Methodological Lessons from the Teamwork Study of Professional Change","authors":"Inge Kryger Pedersen, Anders Blok","doi":"10.1177/00811750241228597","DOIUrl":"https://doi.org/10.1177/00811750241228597","url":null,"abstract":"The authors argue that hitherto separate methodological conversations about abduction and comparison can be fruitfully brought together to generate novel, well-founded insights and retheorize an object of study in multiple-case qualitative inquiry. The authors call this abductive cross-case comparison and illustrate it by way of a collective study of how professional boundary work is changing under transnational conditions. In this study, the authors faced a common challenge in qualitative-comparative research: what to do when initial observations generate “surprises” that seem to confound the theoretical frameworks undergirding the comparison? To discuss how abductive inferences supported the authors’ response to this challenge, they explicate the acts of discovery and (re)conceptualization involved through various steps in a team-based research process. Building on the existing qualitative comparison literature, the authors suggest that such procedures fill a methodological gap and may hold great promise for overcoming obstacles in designing and implementing comparative research. Overall, the authors explicate and illustrate the method of abductive cross-case comparison, including their work as a research team. The aim of this article is thus to help sociologists implement better qualitative research that leverages a fuller potential of comparative designs to push beyond established knowledge and frameworks.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842125","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 : 2024-02-05DOI: 10.1177/00811750231220950
Scott W. Duxbury
Mediation analysis is increasingly used in the social sciences. Extension to social network data, however, has proved difficult because statistical network models are formulated at a lower level of analysis (the dyad) than many outcomes of interest. This study introduces a general approach for micro-macro mediation analysis in social networks. The author defines the average mediated micro effect (AMME) as the indirect effect of a network selection process on an individual, group, or organizational outcome through its effect on an intervening network variable. The author shows that the AMME can be nonparametrically identified using a wide range of common statistical network and regression modeling strategies under the assumption of conditional independence among multiple mediators. Nonparametric and parametric algorithms are introduced to generically estimate the AMME in a multitude of research designs. The author illustrates the utility of the method with an applied example using cross-sectional National Longitudinal Study of Adolescent to Adult Health data to examine the friendship selection mechanisms that indirectly shape adolescent school performance through their effect on network structure.
{"title":"Micro-Macro Mediation Analysis in Social Networks","authors":"Scott W. Duxbury","doi":"10.1177/00811750231220950","DOIUrl":"https://doi.org/10.1177/00811750231220950","url":null,"abstract":"Mediation analysis is increasingly used in the social sciences. Extension to social network data, however, has proved difficult because statistical network models are formulated at a lower level of analysis (the dyad) than many outcomes of interest. This study introduces a general approach for micro-macro mediation analysis in social networks. The author defines the average mediated micro effect (AMME) as the indirect effect of a network selection process on an individual, group, or organizational outcome through its effect on an intervening network variable. The author shows that the AMME can be nonparametrically identified using a wide range of common statistical network and regression modeling strategies under the assumption of conditional independence among multiple mediators. Nonparametric and parametric algorithms are introduced to generically estimate the AMME in a multitude of research designs. The author illustrates the utility of the method with an applied example using cross-sectional National Longitudinal Study of Adolescent to Adult Health data to examine the friendship selection mechanisms that indirectly shape adolescent school performance through their effect on network structure.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864629","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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