Pub Date : 2022-01-27DOI: 10.1177/00491241211043140
Sarah K. Cowan, M. Hout, Stuart Perrett
Long-running surveys need a systematic way to reflect social change and to keep items relevant to respondents, especially when they ask about controversial subjects, or they threaten the items’ validity. We propose a protocol for updating measures that preserves content and construct validity. First, substantive experts articulate the current and anticipated future terms of debate. Then survey experts use this substantive input and their knowledge of existing measures to develop and pilot a large battery of new items. Third, researchers analyze the pilot data to select items for the survey of record. Finally, the items appear on the survey-of-record, available to the whole user community. Surveys-of-record have procedures for changing content that determine if the new items appear just once or become part of the core. We provide the example of developing new abortion attitude measures in the General Social Survey. Current questions ask whether abortion should be legal under varying circumstances. The new abortion items ask about morality, access, state policy, and interpersonal dynamics. They improve content and construct validity and add new insights into Americans’ abortion attitudes.
{"title":"Updating a Time-Series of Survey Questions: The Case of Abortion Attitudes in the General Social Survey","authors":"Sarah K. Cowan, M. Hout, Stuart Perrett","doi":"10.1177/00491241211043140","DOIUrl":"https://doi.org/10.1177/00491241211043140","url":null,"abstract":"Long-running surveys need a systematic way to reflect social change and to keep items relevant to respondents, especially when they ask about controversial subjects, or they threaten the items’ validity. We propose a protocol for updating measures that preserves content and construct validity. First, substantive experts articulate the current and anticipated future terms of debate. Then survey experts use this substantive input and their knowledge of existing measures to develop and pilot a large battery of new items. Third, researchers analyze the pilot data to select items for the survey of record. Finally, the items appear on the survey-of-record, available to the whole user community. Surveys-of-record have procedures for changing content that determine if the new items appear just once or become part of the core. We provide the example of developing new abortion attitude measures in the General Social Survey. Current questions ask whether abortion should be legal under varying circumstances. The new abortion items ask about morality, access, state policy, and interpersonal dynamics. They improve content and construct validity and add new insights into Americans’ abortion attitudes.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41519369","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 : 2022-01-25DOI: 10.1177/00491241211036153
Tim Haesebrouck
The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA’s main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated way, in order to get as much information as possible on the causal structure behind the phenomenon under investigation. The parsimonious solution is capable of identifying causally relevant conditions, the conservative solution of identifying contextually irrelevant conditions. In addition to conditions for which the data provide evidence that they are causally relevant or contextually irrelevant, there will be conditions for which the data neither suggest that they are relevant nor contextually irrelevant. In line with the procedure for crafting the intermediate solution, it is possible to make clear for which of these ambiguous conditions it is not plausible that they are relevant in the context of the research.
{"title":"Relevant, Irrelevant, or Ambiguous? Toward a New Interpretation of QCA’s Solution Types","authors":"Tim Haesebrouck","doi":"10.1177/00491241211036153","DOIUrl":"https://doi.org/10.1177/00491241211036153","url":null,"abstract":"The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA’s main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated way, in order to get as much information as possible on the causal structure behind the phenomenon under investigation. The parsimonious solution is capable of identifying causally relevant conditions, the conservative solution of identifying contextually irrelevant conditions. In addition to conditions for which the data provide evidence that they are causally relevant or contextually irrelevant, there will be conditions for which the data neither suggest that they are relevant nor contextually irrelevant. In line with the procedure for crafting the intermediate solution, it is possible to make clear for which of these ambiguous conditions it is not plausible that they are relevant in the context of the research.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45282212","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 : 2022-01-19DOI: 10.1177/00491241211055764
Julia Meisters, Adrian Hoffmann, J. Musch
Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting instruction non-adherence, and similar to the Triangular Model, it uses simplified instructions to improve respondents’ understanding of the procedure. Based on a comparison with the known prevalence of a sensitive attribute serving as external criterion, we report the first individual-level validation of the Cheating Detection Model, the Triangular Model and the Cheating Detection Triangular Model. Moreover, the sensitivity and specificity of all models was assessed, as well as the respondents’ subjective evaluation of all questioning technique formats. Based on our results, the Cheating Detection Triangular Model appears to be the best choice among the investigated indirect questioning techniques.
{"title":"A New Approach to Detecting Cheating in Sensitive Surveys: The Cheating Detection Triangular Model","authors":"Julia Meisters, Adrian Hoffmann, J. Musch","doi":"10.1177/00491241211055764","DOIUrl":"https://doi.org/10.1177/00491241211055764","url":null,"abstract":"Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting instruction non-adherence, and similar to the Triangular Model, it uses simplified instructions to improve respondents’ understanding of the procedure. Based on a comparison with the known prevalence of a sensitive attribute serving as external criterion, we report the first individual-level validation of the Cheating Detection Model, the Triangular Model and the Cheating Detection Triangular Model. Moreover, the sensitivity and specificity of all models was assessed, as well as the respondents’ subjective evaluation of all questioning technique formats. Based on our results, the Cheating Detection Triangular Model appears to be the best choice among the investigated indirect questioning techniques.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43947881","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 : 2022-01-17DOI: 10.1177/00491241211043138
Fabiola Reiber, D. Bryce, R. Ulrich
Randomized response techniques (RRTs) are applied to reduce response biases in self-report surveys on sensitive research questions (e.g., on socially undesirable characteristics). However, there is evidence that they cannot completely eliminate self-protecting response strategies. To address this problem, there are RRTs specifically designed to measure the extent of such strategies. Here we assessed the recently devised unrelated question model—cheating extension (UQMC) in a preregistered online survey on intimate partner violence (IPV) victimization and perpetration during the first contact restrictions as containment measures for the outbreak of the coronavirus disease 2019 pandemic in Germany in early 2020. The UQMC accounting for self-protecting responses described the data better than its predecessor model which assumes instruction adherence. The resulting three-month prevalence estimates were about 10% and we found a high proportion of self-protecting responses in the group of female participants queried about IPV victimization. However, unexpected results concerning the differences in prevalence estimates across the groups queried about victimization and perpetration highlight the difficulty of investigating sensitive research questions even using methods that guarantee anonymity and the importance of interpreting the respective estimates with caution.
{"title":"Self-protecting responses in randomized response designs: A survey on intimate partner violence during the coronavirus disease 2019 pandemic","authors":"Fabiola Reiber, D. Bryce, R. Ulrich","doi":"10.1177/00491241211043138","DOIUrl":"https://doi.org/10.1177/00491241211043138","url":null,"abstract":"Randomized response techniques (RRTs) are applied to reduce response biases in self-report surveys on sensitive research questions (e.g., on socially undesirable characteristics). However, there is evidence that they cannot completely eliminate self-protecting response strategies. To address this problem, there are RRTs specifically designed to measure the extent of such strategies. Here we assessed the recently devised unrelated question model—cheating extension (UQMC) in a preregistered online survey on intimate partner violence (IPV) victimization and perpetration during the first contact restrictions as containment measures for the outbreak of the coronavirus disease 2019 pandemic in Germany in early 2020. The UQMC accounting for self-protecting responses described the data better than its predecessor model which assumes instruction adherence. The resulting three-month prevalence estimates were about 10% and we found a high proportion of self-protecting responses in the group of female participants queried about IPV victimization. However, unexpected results concerning the differences in prevalence estimates across the groups queried about victimization and perpetration highlight the difficulty of investigating sensitive research questions even using methods that guarantee anonymity and the importance of interpreting the respective estimates with caution.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44038506","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 : 2022-01-11DOI: 10.1177/00491241211067513
Michael Schultz
This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering recurrent patterns by employing a more restrictive Markov assumption. The resulting model, which I call the recurrent multinomial model, provides a parsimonious representation of recurrent sequences, enabling the investigation of recurrences on longer time scales than existing models. The utility of recurrent multinomial models is demonstrated by applying them to the case of conversational turn-taking in meetings of the Federal Open Market Committee (FOMC). Analyses are effectively able to discover norms around turn-reclaiming, participation, and suppression and to evaluate how these norms vary throughout the course of the meeting.
{"title":"Recurrent Multinomial Models for Categorical Sequences","authors":"Michael Schultz","doi":"10.1177/00491241211067513","DOIUrl":"https://doi.org/10.1177/00491241211067513","url":null,"abstract":"This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering recurrent patterns by employing a more restrictive Markov assumption. The resulting model, which I call the recurrent multinomial model, provides a parsimonious representation of recurrent sequences, enabling the investigation of recurrences on longer time scales than existing models. The utility of recurrent multinomial models is demonstrated by applying them to the case of conversational turn-taking in meetings of the Federal Open Market Committee (FOMC). Analyses are effectively able to discover norms around turn-reclaiming, participation, and suppression and to evaluate how these norms vary throughout the course of the meeting.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45767592","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 : 2021-12-30DOI: 10.1177/00491241211067514
Laura K. Nelson, R. Getman, S. Haque
Narrating history is perpetually contested, shaping and reshaping how nations and people understand both their pasts and the current moment. Measuring and evaluating the scope of histories is methodologically challenging. In this paper we provide a general approach and a specific method to measure historical recall. Operationalizing historical information as one or more word phrases, we use the phrase-mining RAKE algorithm on a collection of primary historical documents to extract first-person historical evidence, and then measure recall via phrases present on contemporary Wikipedia, taken to represent a publicly-accessible summary of existing knowledge on virtually any historical topic. We demonstrate this method using women's movements in the United States as a case study of a debated historical field. We found that issues important to working-class elements of the movement were less likely to be covered on Wikipedia compared to other subsections of the movement. Combining this method with a qualitative analysis of select articles, we identified a typology of mechanisms leading to historical omissions: paucity, restrictive paradigms, and categorical narrowness. Our approach, we conclude, can be used to both evaluate the recall of a body of history and to actively intervene in enlarging the scope of our histories and historical knowledge.
{"title":"And the Rest is History: Measuring the Scope and Recall of Wikipedia’s Coverage of Three Women’s Movement Subgroups","authors":"Laura K. Nelson, R. Getman, S. Haque","doi":"10.1177/00491241211067514","DOIUrl":"https://doi.org/10.1177/00491241211067514","url":null,"abstract":"Narrating history is perpetually contested, shaping and reshaping how nations and people understand both their pasts and the current moment. Measuring and evaluating the scope of histories is methodologically challenging. In this paper we provide a general approach and a specific method to measure historical recall. Operationalizing historical information as one or more word phrases, we use the phrase-mining RAKE algorithm on a collection of primary historical documents to extract first-person historical evidence, and then measure recall via phrases present on contemporary Wikipedia, taken to represent a publicly-accessible summary of existing knowledge on virtually any historical topic. We demonstrate this method using women's movements in the United States as a case study of a debated historical field. We found that issues important to working-class elements of the movement were less likely to be covered on Wikipedia compared to other subsections of the movement. Combining this method with a qualitative analysis of select articles, we identified a typology of mechanisms leading to historical omissions: paucity, restrictive paradigms, and categorical narrowness. Our approach, we conclude, can be used to both evaluate the recall of a body of history and to actively intervene in enlarging the scope of our histories and historical knowledge.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"51 1","pages":"1788 - 1825"},"PeriodicalIF":6.3,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49416707","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 : 2021-12-14DOI: 10.1177/00491241211055770
J. Cremers, L. Mortensen, C. Ekstrøm
Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.
{"title":"A Joint Model for Longitudinal and Time-to-event Data in Social and Life Course Research: Employment Status and Time to Retirement","authors":"J. Cremers, L. Mortensen, C. Ekstrøm","doi":"10.1177/00491241211055770","DOIUrl":"https://doi.org/10.1177/00491241211055770","url":null,"abstract":"Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41726288","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 : 2021-12-08DOI: 10.1177/00491241211055765
Blaine G. Robbins
The Stranger Face Trust scale (SFT) and Imaginary Stranger Trust scale (IST) are two new self-report measures of generalized trust that assess trust in strangers—both real and imaginary—across four trust domains. Prior research has established the reliability and validity of SFT and IST, but a number of measurement validation tests remain. Across three separate studies, I assess the test–retest reliability, measurement invariance, predictive validity, and replicability of SFT and IST, with the misanthropy scale (MST) and generalized social trust scale (GST) serving as benchmarks. First, tests of internal consistency, test–retest reliability, and longitudinal measurement invariance established that all four generalized trust scales were acceptably reliable, with SFT and IST yielding greater overall reliability than MST and GST. Second, tests of multiple group measurement invariance revealed that SFT and IST were equivalent across gender, race, education, and age groups, while MST and GST were non-equivalent across the same sociodemographic groups. Third, an investment game established the predictive validity of SFT and MST, with IST and GST yielding poor predictive validity. Fourth, tests of factor structure and measurement invariance indicated that all four generalized trust scales replicated across samples. The present findings bolster the validity, reliability, and measurement equivalence of SFT and IST, while illustrating the compromised validity and measurement non-equivalence of MST and GST. Implications for the measurement of generalized trust are discussed.
{"title":"An Empirical Comparison of Four Generalized Trust Scales: Test–Retest Reliability, Measurement Invariance, Predictive Validity, and Replicability","authors":"Blaine G. Robbins","doi":"10.1177/00491241211055765","DOIUrl":"https://doi.org/10.1177/00491241211055765","url":null,"abstract":"The Stranger Face Trust scale (SFT) and Imaginary Stranger Trust scale (IST) are two new self-report measures of generalized trust that assess trust in strangers—both real and imaginary—across four trust domains. Prior research has established the reliability and validity of SFT and IST, but a number of measurement validation tests remain. Across three separate studies, I assess the test–retest reliability, measurement invariance, predictive validity, and replicability of SFT and IST, with the misanthropy scale (MST) and generalized social trust scale (GST) serving as benchmarks. First, tests of internal consistency, test–retest reliability, and longitudinal measurement invariance established that all four generalized trust scales were acceptably reliable, with SFT and IST yielding greater overall reliability than MST and GST. Second, tests of multiple group measurement invariance revealed that SFT and IST were equivalent across gender, race, education, and age groups, while MST and GST were non-equivalent across the same sociodemographic groups. Third, an investment game established the predictive validity of SFT and MST, with IST and GST yielding poor predictive validity. Fourth, tests of factor structure and measurement invariance indicated that all four generalized trust scales replicated across samples. The present findings bolster the validity, reliability, and measurement equivalence of SFT and IST, while illustrating the compromised validity and measurement non-equivalence of MST and GST. Implications for the measurement of generalized trust are discussed.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45705214","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 : 2021-11-29DOI: 10.1177/00491241211043139
Bert Weijters, E. Davidov, H. Baumgartner
In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.
{"title":"Analyzing factorial survey data with structural equation models","authors":"Bert Weijters, E. Davidov, H. Baumgartner","doi":"10.1177/00491241211043139","DOIUrl":"https://doi.org/10.1177/00491241211043139","url":null,"abstract":"In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47376067","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 : 2021-11-17DOI: 10.1177/00491241211043131
R. Breen, J. Ermisch
We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds of post-outcome confounding, and we show the specific situations in which inverse probability weighting will allow us to obtain estimates that are consistent or, if not consistent, less biased than those obtained via ordinary least squares regression.
{"title":"Using Inverse Probability Weighting to Address Post-Outcome Collider Bias","authors":"R. Breen, J. Ermisch","doi":"10.1177/00491241211043131","DOIUrl":"https://doi.org/10.1177/00491241211043131","url":null,"abstract":"We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds of post-outcome confounding, and we show the specific situations in which inverse probability weighting will allow us to obtain estimates that are consistent or, if not consistent, less biased than those obtained via ordinary least squares regression.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48294582","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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