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The gap-closing estimand: A causal approach to study interventions that close disparities across social categories. 差距缩小估计：研究消除社会类别差异的干预措施的一种因果方法。
IF 6.5 2区 社会学
Sociological Methods & Research Pub Date : 2024-05-01 Epub Date: 2022-01-13 DOI: 10.1177/00491241211055769
Ian Lundberg
{"title":"The gap-closing estimand: A causal approach to study interventions that close disparities across social categories.","authors":"Ian Lundberg","doi":"10.1177/00491241211055769","DOIUrl":"10.1177/00491241211055769","url":null,"abstract":"<p><p>Disparities across race, gender, and class are important targets of descriptive research. But rather than only describe disparities, research would ideally inform interventions to close those gaps. The gap-closing estimand quantifies how much a gap (e.g. incomes by race) would close if we intervened to equalize a treatment (e.g. access to college). Drawing on causal decomposition analyses, this type of research question yields several benefits. First, gap-closing estimands place categories like race in a causal framework without making them play the role of the treatment (which is philosophically fraught for non-manipulable variables). Second, gap-closing estimands empower researchers to study disparities using new statistical and machine learning estimators designed for causal effects. Third, gap-closing estimands can directly inform policy: if we sampled from the population and actually changed treatment assignments, how much could we close gaps in outcomes? I provide open-source software (the R package gapclosing) to support these methods.</p>","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"53 2","pages":"507-570"},"PeriodicalIF":6.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11823715/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415331","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}
引用次数: 0
How Valid Are Trust Survey Measures? New Insights From Open-Ended Probing Data and Supervised Machine Learning 信任调查措施的有效性如何？来自开放式探测数据和监督机器学习的新见解
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2024-03-21 DOI: 10.1177/00491241241234871
Camille Landesvatter, Paul C. Bauer
{"title":"How Valid Are Trust Survey Measures? New Insights From Open-Ended Probing Data and Supervised Machine Learning","authors":"Camille Landesvatter, Paul C. Bauer","doi":"10.1177/00491241241234871","DOIUrl":"https://doi.org/10.1177/00491241241234871","url":null,"abstract":"Trust is a foundational concept of contemporary sociological theory. Still, empirical research on trust relies on a relatively small set of measures. These are increasingly debated, potentially undermining large swathes of empirical evidence. Drawing on a combination of open-ended probing data, supervised machine learning, and a U.S. representative quota sample, our study compares the validity of standard measures of generalized social trust with more recent, situation-specific measures of trust. We find that survey measures that refer to “strangers” in their question wording best reflect the concept of generalized trust, also known as trust in unknown others. While situation-specific measures should have the desirable property of further reducing variation in associations, that is, producing more similar frames of reference across respondents, they also seem to increase associations with known others, which is undesirable. In addition, we explore to what extent trust survey questions may evoke negative associations. We find that there is indeed variation across measures, which calls for more research.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"78 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140192831","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}
引用次数: 0
Data Imbalances in Coincidence Analysis: A Simulation Study 巧合分析中的数据失衡：模拟研究
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2024-03-19 DOI: 10.1177/00491241241227039
Martyna Daria Swiatczak, Michael Baumgartner
{"title":"Data Imbalances in Coincidence Analysis: A Simulation Study","authors":"Martyna Daria Swiatczak, Michael Baumgartner","doi":"10.1177/00491241241227039","DOIUrl":"https://doi.org/10.1177/00491241241227039","url":null,"abstract":"In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data imbalances, when not combined with fragmentation or noise, do not negatively affect CNA’s performance. However, an extended series of simulation experiments on fuzzy-set data reveals that, when mixed with fragmentation or noise, data imbalances may substantially impair CNA’s performance. Furthermore, we find that the performance impairment is higher when endogenous factors are imbalanced than when exogenous factors are concerned. Our results allow us to quantify these impacts and demarcate degrees at which data imbalances should be considered as problematic. Thus, applied researchers can use our demarcation guidelines to enhance the validity of their studies.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"27 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140165080","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}
引用次数: 0
A Tool Kit for Relation Induction in Text Analysis 文本分析中的关系诱导工具包
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2024-02-29 DOI: 10.1177/00491241241233242
Dustin S. Stoltz, Marshall A. Taylor, Jennifer S. K. Dudley
{"title":"A Tool Kit for Relation Induction in Text Analysis","authors":"Dustin S. Stoltz, Marshall A. Taylor, Jennifer S. K. Dudley","doi":"10.1177/00491241241233242","DOIUrl":"https://doi.org/10.1177/00491241241233242","url":null,"abstract":"Distances derived from word embeddings can measure a range of gradational relations—similarity, hierarchy, entailment, and stereotype—and can be used at the document- and author-level in ways that overcome some of the limitations of weighted dictionary methods. We provide a comprehensive introduction to using word embeddings for relation induction, and demonstrate how such techniques can complement dictionary methods as unsupervised, deductive methods.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"46 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140015572","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}
引用次数: 0
Occupational Percentile Rank: A New Method for Constructing a Socioeconomic Index of Occupational Status 职业百分位排名:构建职业地位社会经济指标的新方法
2区 社会学
Sociological Methods & Research Pub Date : 2023-11-09 DOI: 10.1177/00491241231207914
Xi Song, Yu Xie
{"title":"Occupational Percentile Rank: A New Method for Constructing a Socioeconomic Index of Occupational Status","authors":"Xi Song, Yu Xie","doi":"10.1177/00491241231207914","DOIUrl":"https://doi.org/10.1177/00491241231207914","url":null,"abstract":"In this paper, we propose a method for constructing an occupation-based socioeconomic index that can easily incorporate changes in occupational structure. The resulting index is the occupational percentile rank for a given cohort, based on contemporaneous information pertaining to educational composition and the number of workers at the occupation level. An occupation may experience an increase or decrease in its occupational rank due to changes in relative sizes and educational compositions across occupations. The method is flexible in dealing with changes in occupational and educational measurements over time. Applying the method to U.S. history from the mid-nineteenth century to the present day, we derive the index using IPUMS U.S. Census microdata from 1850 to 2000 and the American Community Surveys (ACSs) from 2001 to 2018. Compared to previous occupational measures, this new measure takes into account occupational status evolvement caused by long-term secular changes in occupational size and educational composition. The resulting percentile rank measure can be easily merged with social surveys and administrative data that include occupational measures based on the U.S. Census occupation codes and crosswalks.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135286393","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}
引用次数: 0
Marginal and Conditional Confounding Using Logits. 使用逻辑的边际和条件混淆
IF 6.5 2区 社会学
Sociological Methods & Research Pub Date : 2023-11-01 Epub Date: 2021-04-09 DOI: 10.1177/0049124121995548
Kristian Bernt Karlson, Frank Popham, Anders Holm
{"title":"Marginal and Conditional Confounding Using Logits.","authors":"Kristian Bernt Karlson, Frank Popham, Anders Holm","doi":"10.1177/0049124121995548","DOIUrl":"10.1177/0049124121995548","url":null,"abstract":"<p><p>This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of confounding (marginal and conditional) that can be recovered from a simple standardization approach. We investigate when marginal and conditional confounding may differ, outline why the method by Karlson, Holm, and Breen recovers conditional confounding under a \"no interaction\"-assumption, and suggest that researchers may measure marginal confounding by using inverse probability weighting. We provide two empirical examples that illustrate our standardization approach.</p>","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"1 1","pages":"1765-1784"},"PeriodicalIF":6.5,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42412945","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}
引用次数: 0
High-Dimensional Imputation for the Social Sciences: A Comparison of State-of-The-Art Methods 社会科学的高维归算:最新方法的比较
2区 社会学
Sociological Methods & Research Pub Date : 2023-09-16 DOI: 10.1177/00491241231200194
Edoardo Costantini, Kyle M. Lang, Tim Reeskens, Klaas Sijtsma
{"title":"High-Dimensional Imputation for the Social Sciences: A Comparison of State-of-The-Art Methods","authors":"Edoardo Costantini, Kyle M. Lang, Tim Reeskens, Klaas Sijtsma","doi":"10.1177/00491241231200194","DOIUrl":"https://doi.org/10.1177/00491241231200194","url":null,"abstract":"Including a large number of predictors in the imputation model underlying a multiple imputation (MI) procedure is one of the most challenging tasks imputers face. A variety of high-dimensional MI techniques can help, but there has been limited research on their relative performance. In this study, we investigated a wide range of extant high-dimensional MI techniques that can handle a large number of predictors in the imputation models and general missing data patterns. We assessed the relative performance of seven high-dimensional MI methods with a Monte Carlo simulation study and a resampling study based on real survey data. The performance of the methods was defined by the degree to which they facilitate unbiased and confidence-valid estimates of the parameters of complete data analysis models. We found that using lasso penalty or forward selection to select the predictors used in the MI model and using principal component analysis to reduce the dimensionality of auxiliary data produce the best results.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135308604","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}
引用次数: 3
Current and Future Debates in Video Data Analysis 视频数据分析中当前和未来的争论
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-06-08 DOI: 10.1177/00491241231178275
Nicolas M. Legewie, Anne Nassauer
{"title":"Current and Future Debates in Video Data Analysis","authors":"Nicolas M. Legewie, Anne Nassauer","doi":"10.1177/00491241231178275","DOIUrl":"https://doi.org/10.1177/00491241231178275","url":null,"abstract":"Video-based social science research is thriving. Across disciplines and topic areas, researchers use twenty-first century video data to gain novel insights into how social processes and events unfold on the ground. In recent years, “video data analysis” (VDA) has emerged as a methodological framework to facilitate this type of video-based research. The special issue “The Present and Future of Video-based Social Science Research: Innovations in Video Data Analysis” presents methodological innovations that speak to some of the most pressing debates around VDA. Contributions showcase the range of disciplines and research fields VDA is used in, from social interactions and collective behavior to neighborhoods, policing, and public health. This introductory article outlines two areas of growth in VDA methodology that the articles of this special issue speak to: taking advantage of scale and detail in VDA, and situating VDA in the canon of research methods.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"1107 - 1119"},"PeriodicalIF":6.3,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42172410","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}
引用次数: 0
Graphical Causal Models for Survey Inference 调查推断的图形因果模型
2区 社会学
Sociological Methods & Research Pub Date : 2023-05-30 DOI: 10.1177/00491241231176851
Julian Schuessler, Peter Selb
{"title":"Graphical Causal Models for Survey Inference","authors":"Julian Schuessler, Peter Selb","doi":"10.1177/00491241231176851","DOIUrl":"https://doi.org/10.1177/00491241231176851","url":null,"abstract":"Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of bias and assumptions for eliminating it in various selection scenarios. We then introduce and analyze graphical representations of multiple selection stages in the data collection process, and highlight the strong assumptions implicit in using only design weights. Furthermore, we show that the common practice of selecting adjustment variables based on correlations with sample selection and outcome variables of interest is ill-justified and that nonresponse weighting when the interest is in causal inference may come at severe costs. Finally, we identify further areas for survey methodology research that can benefit from advances in causal graph theory.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135479071","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}
引用次数: 1
Linear Probability Model Revisited: Why It Works and How It Should Be Specified 重新审视线性概率模型:它为什么工作以及它应该如何被指定
2区 社会学
Sociological Methods & Research Pub Date : 2023-05-29 DOI: 10.1177/00491241231176850
Myoung-jae Lee, Goeun Lee, Jin-young Choi
{"title":"Linear Probability Model Revisited: Why It Works and How It Should Be Specified","authors":"Myoung-jae Lee, Goeun Lee, Jin-young Choi","doi":"10.1177/00491241231176850","DOIUrl":"https://doi.org/10.1177/00491241231176850","url":null,"abstract":"A linear model is often used to find the effect of a binary treatment [Formula: see text] on a noncontinuous outcome [Formula: see text] with covariates [Formula: see text]. Particularly, a binary [Formula: see text] gives the popular “linear probability model (LPM),” but the linear model is untenable if [Formula: see text] contains a continuous regressor. This raises the question: what kind of treatment effect does the ordinary least squares estimator (OLS) to LPM estimate? This article shows that the OLS estimates a weighted average of the [Formula: see text]-conditional heterogeneous effect plus a bias. Under the condition that [Formula: see text] is equal to the linear projection of [Formula: see text] on [Formula: see text], the bias becomes zero, and the OLS estimates the “overlap-weighted average” of the [Formula: see text]-conditional effect. Although the condition does not hold in general, specifying the [Formula: see text]-part of the LPM such that the [Formula: see text]-part predicts [Formula: see text] well, not [Formula: see text], minimizes the bias counter-intuitively. This article also shows how to estimate the overlap-weighted average without the condition by using the “propensity-score residual” [Formula: see text]. An empirical analysis demonstrates our points.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135791840","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}
引用次数: 0
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