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Marginal and Conditional Confounding Using Logits. 使用逻辑的边际和条件混淆
IF 6.3 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,&nbsp;Frank Popham,&nbsp;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":6.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0049124121995548","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: 6
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
Curating Training Data for Reliable Large-Scale Visual Data Analysis: Lessons from Identifying Trash in Street View Imagery 为可靠的大规模视觉数据分析策划训练数据:从街景图像中识别垃圾的经验教训
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-05-15 DOI: 10.1177/00491241231171945
Jackelyn Hwang, Nima Dahir, Mayuka Sarukkai, Gabby Wright
{"title":"Curating Training Data for Reliable Large-Scale Visual Data Analysis: Lessons from Identifying Trash in Street View Imagery","authors":"Jackelyn Hwang, Nima Dahir, Mayuka Sarukkai, Gabby Wright","doi":"10.1177/00491241231171945","DOIUrl":"https://doi.org/10.1177/00491241231171945","url":null,"abstract":"Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze these data with existing approaches limit their use. Computer vision methods hold promise but often require large and nonexistent training data to identify sociologically relevant variables. We present a cost-efficient method for curating training data that utilizes simple tasks and pairwise comparisons to interpret and analyze visual data at scale using computer vision. We apply our approach to the detection of trash levels across space and over time in millions of street-level images in three physically distinct US cities. By comparing to ratings produced in a controlled setting and utilizing computational methods, we demonstrate generally high reliability in the method and identify sources that limit it. Altogether, this approach expands how visual data can be used at a large scale in sociology.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"1155 - 1200"},"PeriodicalIF":6.3,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41859082","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 Method for Estimating Individual Socioeconomic Status of Twitter Users 一种估算Twitter用户个人社会经济地位的方法
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-04-16 DOI: 10.1177/00491241231168665
Yuanmo He, Milena Tsvetkova
{"title":"A Method for Estimating Individual Socioeconomic Status of Twitter Users","authors":"Yuanmo He, Milena Tsvetkova","doi":"10.1177/00491241231168665","DOIUrl":"https://doi.org/10.1177/00491241231168665","url":null,"abstract":"The rise of social media has opened countless opportunities to explore social science questions with new data and methods. However, research on socioeconomic inequality remains constrained by limit...","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"51 27","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167294","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
The Effects of Omitting Components in a Multilevel Model With Social Network Effects 具有社会网络效应的多层次模型中省略成分的影响
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-03-15 DOI: 10.1177/00491241231156972
Thomas Suesse, David Steel, Mark Tranmer
{"title":"The Effects of Omitting Components in a Multilevel Model With Social Network Effects","authors":"Thomas Suesse, David Steel, Mark Tranmer","doi":"10.1177/00491241231156972","DOIUrl":"https://doi.org/10.1177/00491241231156972","url":null,"abstract":"Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associat...","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"43 4","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167456","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
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Optimal Transport and Conformal Prediction Sets 利用最优传输和保形预测集提高刑事司法算法风险评估公平性
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-03-13 DOI: 10.1177/00491241231155883
Richard A. Berk, Arun Kumar Kuchibhotla, Eric Tchetgen Tchetgen
{"title":"Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Optimal Transport and Conformal Prediction Sets","authors":"Richard A. Berk, Arun Kumar Kuchibhotla, Eric Tchetgen Tchetgen","doi":"10.1177/00491241231155883","DOIUrl":"https://doi.org/10.1177/00491241231155883","url":null,"abstract":"In the United States and elsewhere, risk assessment algorithms are being used to help inform criminal justice decision-makers. A common intent is to forecast an offender’s “future dangerousness.” S...","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"42 6","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167459","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: 2
Video Data Analysis and Police Body-Worn Camera Footage 视频数据分析与警用人体摄像镜头
IF 6.3 2区 社会学
Sociological Methods & Research Pub Date : 2023-02-20 DOI: 10.1177/00491241231156968
John D. McCluskey, Craig D. Uchida
{"title":"Video Data Analysis and Police Body-Worn Camera Footage","authors":"John D. McCluskey, Craig D. Uchida","doi":"10.1177/00491241231156968","DOIUrl":"https://doi.org/10.1177/00491241231156968","url":null,"abstract":"Video data analysis (VDA) represents an important methodological framework for contemporary research approaches to the myriad of footage available from cameras, devices, and phones. Footage from police body-worn cameras (BWCs) is anticipated to be a widely available platform for social science researchers to scrutinize the interactions between police and citizens. We examine issues of validity and reliability as related to BWCs in the context of VDA, based on an assessment of the quality of audio and video obtained from that platform. Second, we compare the coding of BWC footage obtained from a sample of police-citizen encounters to coding of the same events by on-scene coders using an instrument adapted from in-person systematic social observations (SSOs). Findings show that there are substantial and systematic audio and video gaps present in BWC footage as a source of data for social science investigation that likely impact the reliability of measures. Despite these problems, BWC data have substantial capacity for judging sequential developments, causal ordering, and the duration of events. Thus, the technology should open theoretical frames that are too cumbersome for in-person observation. Theoretical development with VDA in mind is suggested as an important pathway for future researchers in terms of framing data collection from BWCs and also suggesting areas where triangulation is essential.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"1120 - 1154"},"PeriodicalIF":6.3,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42377767","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: 2
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