Sociological Methods & Research最新文献

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Untapped Potential: Designed Digital Trace Data in Online Survey Experiments 未开发的潜力：在线调查实验中设计的数字痕迹数据

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-08-09 DOI: 10.1177/00491241241268770

Erin Macke, Claire Daviss, Emma Williams-Baron

Researchers have developed many uses for digital trace data, yet most online survey experiments continue to rely on attitudinal rather than behavioral measures. We argue that researchers can collect digital trace data during online survey experiments with relative ease, at modest costs, and to substantial benefit. Because digital trace data unobtrusively measure survey participants’ behaviors, they can be used to analyze digital outcomes of theoretical and empirical interest, while reducing the risk of social desirability bias. We demonstrate the feasibility and utility of collecting digital trace data during online survey experiments through two original studies. In both, participants evaluated interactive digital resumes designed to track participants’ clicks, mouse movements, and time spent on the resumes. This novel approach allowed us to better understand participants’ search for information and cognitive processing in hiring decisions. There is immense, untapped potential value in collecting digital trace data during online survey experiments and using it to address important sociological research questions.

研究人员已经开发了许多数字跟踪数据的用途，但大多数在线调查实验仍然依赖于态度测量而非行为测量。我们认为，在在线调查实验中，研究人员可以相对轻松地收集数字跟踪数据，成本不高，却能获得巨大收益。由于数字跟踪数据可以不引人注意地测量调查参与者的行为，因此可以用来分析理论和实证研究中感兴趣的数字结果，同时降低社会可取性偏差的风险。我们通过两项原创研究证明了在在线调查实验中收集数字跟踪数据的可行性和实用性。在这两项研究中，参与者对互动式数字简历进行了评估，旨在跟踪参与者的点击、鼠标移动以及在简历上花费的时间。这种新颖的方法使我们能够更好地了解参与者在招聘决策中的信息搜索和认知处理过程。在在线调查实验中收集数字跟踪数据，并将其用于解决重要的社会学研究问题，具有巨大的、尚未开发的潜在价值。

引用次数: 0

Handle with Care: A Sociologist’s Guide to Causal Inference with Instrumental Variables 小心处理：社会学家工具变量因果推理指南

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-08-09 DOI: 10.1177/00491241241235900

Chris Felton, Brandon M. Stewart

Instrumental variables (IV) analysis is a powerful, but fragile, tool for drawing causal inferences from observational data. Sociologists increasingly turn to this strategy in settings where unmeasured confounding between the treatment and outcome is likely. This paper reviews the assumptions required for IV and the consequences of violating them, focusing on sociological applications. We highlight three methodological problems IV faces: (i) identification bias, an asymptotic bias from assumption violations; (ii) estimation bias, a finite-sample bias that persists even when assumptions hold; and (iii) type-M error, the exaggeration of effect size given statistical significance. In each case, we emphasize how weak instruments exacerbate these problems and make results sensitive to minor violations of assumptions. We survey IV papers from top sociology journals, finding that assumptions often go unstated and robust uncertainty measures are rarely used. We provide a practical checklist to show how IV, despite its fragility, can still be useful when handled with care.

工具变量（IV）分析是从观察数据中得出因果推论的一种强大但脆弱的工具。在治疗与结果之间可能存在未测量混杂因素的情况下，社会学家越来越多地采用这种策略。本文以社会学应用为重点，回顾了 IV 所需的假设以及违反这些假设的后果。我们强调了 IV 所面临的三个方法问题：(i) 识别偏差，即违反假设产生的渐近偏差；(ii) 估计偏差，即即使假设成立也会持续存在的有限样本偏差；(iii) M 型误差，即在统计显著性条件下夸大效应大小。在每种情况下，我们都会强调弱工具会如何加剧这些问题，并使结果对微小的违反假设的情况变得敏感。我们调查了顶级社会学期刊中的 IV 篇论文，发现这些论文往往没有说明假设，也很少使用稳健的不确定性测量方法。我们提供了一份实用的核对表，说明尽管 IV 很脆弱，但只要小心处理，它仍然是有用的。

引用次数: 0

Age, Period, and Cohort Analysis With Bounding and Interactions 具有边界和交互作用的年龄、时期和队列分析

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-08-02 DOI: 10.1177/00491241241266279

Jiwon Lee

This article uses the example of voter turnout in US presidential elections to compare two new methods for age, period, and cohort (APC) analysis: the APC interaction model and the APC bounding analysis. While discussing the formal, conceptual, and interpretive differences between the two methods, the analysis demonstrates how both methods can be used to generate distinct but complementary findings. Because the two methods take alternative positions on the appropriate cohort-effect estimands, the comparison underscores the importance of well-grounded conceptual foundations in APC analysis.

本文以美国总统选举中的投票率为例，比较了年龄、时期和队列（APC）分析的两种新方法：APC 交互模型和 APC 边界分析。在讨论这两种方法在形式、概念和解释上的差异的同时，分析还展示了如何利用这两种方法得出不同但互补的结论。由于这两种方法对适当的队列效应估计值采取了不同的立场，因此这种比较强调了在 APC 分析中扎实的概念基础的重要性。

引用次数: 0

Causal Decomposition Analysis With Time-Varying Mediators: Designing Individualized Interventions to Reduce Social Disparities 具有时变中介因子的因果分解分析：设计个性化干预措施以减少社会差距

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-07-26 DOI: 10.1177/00491241241264562

Soojin Park, Namhwa Lee, Rafael Quintana

Causal decomposition analysis aims to identify risk factors (referred to as “mediators”) that contribute to social disparities in an outcome. Despite promising developments in causal decomposition analysis, current methods are limited to addressing a time-fixed mediator and outcome only, which has restricted our understanding of the causal mechanisms underlying social disparities. In particular, existing approaches largely overlook individual characteristics when designing (hypothetical) interventions to reduce disparities. To address this issue, we extend current longitudinal mediation approaches to the context of disparities research. Specifically, we develop a novel decomposition analysis method that addresses individual characteristics by (a) using optimal dynamic treatment regimes (DTRs) and (b) conditioning on a selective set of individual characteristics. Incorporating optimal DTRs into the design of interventions can be used to strike a balance between equity (reducing disparities) and excellence (improving individuals’ outcomes). We illustrate the proposed method using the High School Longitudinal Study data.

因果分解分析的目的是找出导致结果出现社会差异的风险因素（称为 "中介因素"）。尽管因果分解分析的发展前景广阔，但目前的方法仅限于处理时间固定的中介因素和结果，这限制了我们对社会差异背后因果机制的理解。特别是，在设计（假设的）干预措施以减少差异时，现有方法在很大程度上忽略了个体特征。为了解决这个问题，我们将目前的纵向调解方法扩展到差异研究中。具体来说，我们开发了一种新颖的分解分析方法，通过（a）使用最优动态治疗制度（DTR）和（b）对一组有选择性的个体特征进行调节来解决个体特征问题。将最佳动态治疗方案纳入干预措施的设计中，可以在公平（减少差异）和卓越（改善个人结果）之间取得平衡。我们使用高中纵向研究数据来说明所建议的方法。

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引用次数: 0

Corrigendum to “Individual Components of Three Inequality Measures for Analyzing Shapes of Inequality” 对 "用于分析不平等形状的三种不平等衡量标准的各个组成部分 "的更正

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-06-20 DOI: 10.1177/00491241241263701

引用次数: 0

The Potential for Using a Shortened Version of the Everyday Discrimination Scale in Population Research with Young Adults: A Construct Validation Investigation. 在年轻人人口研究中使用简化版日常歧视量表的潜力：一项结构验证调查

IF 6.3 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-05-01 Epub Date: 2022-02-07 DOI: 10.1177/00491241211067512

Aprile D Benner, Shanting Chen, Celeste C Fernandez, Mark D Hayward

Discrimination is associated with numerous psychological health outcomes over the life course. The nine-item Everyday Discrimination Scale (EDS) is one of the most widely used measures of discrimination; however, this nine-item measure may not be feasible in large-scale population health surveys where a shortened discrimination measure would be advantageous. The current study examined the construct validity of a combined two-item discrimination measure adapted from the EDS by Add Health (N = 14,839) as compared to the full nine-item EDS and a two-item EDS scale (parallel to the adapted combined measure) used in the National Survey of American Life (NSAL; N = 1,111) and National Latino and Asian American Study (NLAAS) studies (N = 1,055). Results identified convergence among the EDS scales, with high item-total correlations, convergent validity, and criterion validity for psychological outcomes, thus providing evidence for the construct validity of the two-item combined scale. Taken together, the findings provide support for using this reduced scale in studies where the full EDS scale is not available.

歧视与一生中许多心理健康结果有关。九项日常歧视量表是最广泛使用的歧视衡量标准之一；然而，在大规模的人口健康调查中，这项九项措施可能不可行，因为缩短歧视措施是有利的。目前的研究通过添加健康（N = 14839），与美国国家生活调查（NSAL；N = 1111）和全国拉丁裔和亚裔美国人研究（NLAAS）研究（N = 1055）。结果表明，EDS量表具有较高的项目总相关性、收敛有效性和心理结果的标准有效性，从而为两项目组合量表的结构有效性提供了证据。总之，这些发现为在没有完整EDS量表的研究中使用这种缩减的量表提供了支持。

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引用次数: 0

The gap-closing estimand: A causal approach to study interventions that close disparities across social categories.

IF 6.5 2区社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-05-01 Epub Date: 2022-01-13 DOI: 10.1177/00491241211055769

Ian Lundberg

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.

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 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-03-21 DOI: 10.1177/00491241241234871

Camille Landesvatter, Paul C. Bauer

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.

信任是当代社会学理论的一个基础概念。然而，关于信任的实证研究依赖于一套相对较少的衡量标准。对这些指标的争论越来越多，可能会破坏大量的经验证据。我们的研究将开放式探究数据、监督机器学习和美国代表性配额样本相结合，比较了一般社会信任的标准测量方法与最新的、针对具体情况的信任测量方法的有效性。我们发现，在问题措辞中提及 "陌生人 "的调查措施最能反映普遍信任（也称为对未知他人的信任）的概念。虽然针对具体情况的测量方法应具有进一步减少关联差异的理想特性，即在不同受访者之间产生更相似的参照框架，但它们似乎也增加了与已知他人的关联，这是不可取的。此外，我们还探讨了信任调查问题在多大程度上会引起负面联想。我们发现，不同的测量方法确实存在差异，这就需要进行更多的研究。

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 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-03-19 DOI: 10.1177/00491241241227039

Martyna Daria Swiatczak, Michael Baumgartner

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.

在本文中，我们研究了数据不平衡（因子值分布不均时出现的一种常见数据特征）在什么条件下会对巧合分析（CNA）的性能造成问题。我们进一步研究了这种不平衡与数据碎片和噪声的关系。我们的研究表明，即使是极端的数据不平衡，如果不与碎片或噪声结合在一起，也不会对 CNA 的性能产生负面影响。然而，对模糊集数据进行的一系列扩展模拟实验表明，当数据与碎片或噪声混合在一起时，数据不平衡可能会严重影响 CNA 的性能。此外，我们还发现，当内生因素不平衡时，性能受损程度要高于外生因素。我们的研究结果使我们能够量化这些影响，并划分出数据不平衡问题的严重程度。因此，应用研究人员可以利用我们的划分准则来提高研究的有效性。

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 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS

Sociological Methods & Research

Pub Date : 2024-02-29 DOI: 10.1177/00491241241233242

Dustin S. Stoltz, Marshall A. Taylor, Jennifer S. K. Dudley

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.

从词嵌入中得出的距离可以衡量一系列渐变关系--相似性、层次、蕴涵和定型--并且可以在文档和作者层面上使用，克服了加权词典方法的一些局限性。我们全面介绍了如何使用词嵌入进行关系归纳，并展示了这种技术如何作为无监督的演绎方法对词典方法进行补充。

引用次数: 0

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