Pub Date : 2021-08-01DOI: 10.1177/00491241211014245
G. Jasso
Inequality often appears in linked pairs of variables. Examples include schooling and income, income and consumption, and wealth and happiness. Consider the famous words of Veblen: “wealth confers honor.” Understanding inequality requires understanding input inequality, outcome inequality, and the relation between the two—in both inequality between persons and inequality between subgroups. This article contributes to the methodological toolkit for studying inequality by developing a framework that makes explicit both input inequality and outcome inequality and by addressing three main associated questions: (1) How do the mechanisms for generating and altering inequality differ across inputs and outcomes? (2) Which have more inequality—inputs or outcomes? (3) Under what conditions, and by what mechanisms, does input inequality affect outcome inequality? Results include the following: First, under specified conditions, distinctive mechanisms govern inequality in inputs and inequality in outcomes. Second, input inequality and outcome inequality can be the same or different; if different, whether inequality is greater among inputs or outcomes depends on the configuration of outcome function, types of inputs, distributional form of and inequality in cardinal inputs, and number of and associations among inputs. Third, the link between input inequality and outcome inequality is multiform; it can be nonexistent, linear, or nonlinear, and if nonlinear, it can be concave or convex. More deeply, this work signals the formidable empirical challenges in studying inequality, but also the fast growing toolbox. For example, even if the outcome distribution is difficult to derive, fundamental theorems on the variance make it possible to analyze the input–outcome inequality connection. Similarly, within specified distributions, the general inequality parameter makes it possible to express results in terms of both measures of overall inequality and measures of subgroup inequality.
{"title":"Linking Input Inequality and Outcome Inequality","authors":"G. Jasso","doi":"10.1177/00491241211014245","DOIUrl":"https://doi.org/10.1177/00491241211014245","url":null,"abstract":"Inequality often appears in linked pairs of variables. Examples include schooling and income, income and consumption, and wealth and happiness. Consider the famous words of Veblen: “wealth confers honor.” Understanding inequality requires understanding input inequality, outcome inequality, and the relation between the two—in both inequality between persons and inequality between subgroups. This article contributes to the methodological toolkit for studying inequality by developing a framework that makes explicit both input inequality and outcome inequality and by addressing three main associated questions: (1) How do the mechanisms for generating and altering inequality differ across inputs and outcomes? (2) Which have more inequality—inputs or outcomes? (3) Under what conditions, and by what mechanisms, does input inequality affect outcome inequality? Results include the following: First, under specified conditions, distinctive mechanisms govern inequality in inputs and inequality in outcomes. Second, input inequality and outcome inequality can be the same or different; if different, whether inequality is greater among inputs or outcomes depends on the configuration of outcome function, types of inputs, distributional form of and inequality in cardinal inputs, and number of and associations among inputs. Third, the link between input inequality and outcome inequality is multiform; it can be nonexistent, linear, or nonlinear, and if nonlinear, it can be concave or convex. More deeply, this work signals the formidable empirical challenges in studying inequality, but also the fast growing toolbox. For example, even if the outcome distribution is difficult to derive, fundamental theorems on the variance make it possible to analyze the input–outcome inequality connection. Similarly, within specified distributions, the general inequality parameter makes it possible to express results in terms of both measures of overall inequality and measures of subgroup inequality.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"50 1","pages":"944 - 1005"},"PeriodicalIF":6.3,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/00491241211014245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41766388","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 : 2021-08-01Epub Date: 2019-09-24DOI: 10.1177/0049124119875957
Sarah Mustillo, Miao Li, Kenneth F Ferraro
Most studies of the early origins of adult health rely on summing dichotomously measured negative exposures to measure childhood misfortune (CM), neglect, adversity, or trauma. There are several limitations to this approach, including that it assumes each exposure carries the same level of risk for a particular outcome. Further, it often leads researchers to dichotomize continuous measures for the sake of creating an additive variable from similar indicators. We propose an alternative approach within the structural equation modeling (SEM) framework that allows differential weighting of the negative exposures and can incorporate dichotomous and continuous observed variables as well as latent variables. Using the Health and Retirement Study data, our analyses compare the traditional approach (i.e., adding indicators) with alternative models and assess their prognostic validity on adult depressive symptoms. Results reveal that parameter estimates using the conventional model likely underestimate the effects of CM on adult health outcomes. Additionally, while the conventional approach inhibits testing for mediation, our model enables testing mediation of both individual CM variables and the cumulative variable. Further, we test whether cumulative CM is moderated by the accumulation of protective factors, which facilitates theoretical advances in life course and social inequality research. The approach presented here is one way to examine the cumulative effects of early exposures while attending to diversity in the types of exposures experienced. Using the SEM framework, this versatile approach could be used to model the accumulation of risk or reward in many other areas of sociology and the social sciences beyond health.
{"title":"Evaluating the Cumulative Impact of Childhood Misfortune: A Structural Equation Modeling Approach.","authors":"Sarah Mustillo, Miao Li, Kenneth F Ferraro","doi":"10.1177/0049124119875957","DOIUrl":"10.1177/0049124119875957","url":null,"abstract":"<p><p>Most studies of the early origins of adult health rely on summing dichotomously measured negative exposures to measure childhood misfortune (CM), neglect, adversity, or trauma. There are several limitations to this approach, including that it assumes each exposure carries the same level of risk for a particular outcome. Further, it often leads researchers to dichotomize continuous measures for the sake of creating an additive variable from similar indicators. We propose an alternative approach within the structural equation modeling (SEM) framework that allows differential weighting of the negative exposures and can incorporate dichotomous and continuous observed variables as well as latent variables. Using the Health and Retirement Study data, our analyses compare the traditional approach (i.e., adding indicators) with alternative models and assess their prognostic validity on adult depressive symptoms. Results reveal that parameter estimates using the conventional model likely underestimate the effects of CM on adult health outcomes. Additionally, while the conventional approach inhibits testing for mediation, our model enables testing mediation of both individual CM variables and the cumulative variable. Further, we test whether cumulative CM is moderated by the accumulation of protective factors, which facilitates theoretical advances in life course and social inequality research. The approach presented here is one way to examine the cumulative effects of early exposures while attending to diversity in the types of exposures experienced. Using the SEM framework, this versatile approach could be used to model the accumulation of risk or reward in many other areas of sociology and the social sciences beyond health.</p>","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"50 3","pages":"1073-1109"},"PeriodicalIF":6.3,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0049124119875957","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39850101","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}
Pub Date : 2021-07-27DOI: 10.1177/00491241211031268
R. Rutten
Uncertainty undermines causal claims; however, the nature of causal claims decides what counts as relevant uncertainty. Empirical robustness is imperative in regularity theories of causality. Regularity theory features strongly in QCA, making its case sensitivity a weakness. Following qualitative comparative analysis (QCA) founder Charles Ragin’s emphasis on ontological realism, this article suggests causality as a power and thus breaks with the ontological determinism of regularity theories. Exercising causal powers makes it possible for human agents to achieve an outcome but does not determine that they will. The article explains how QCA’s truth table analysis “models” possibilistic uncertainty and how crisp sets do this better than fuzzy sets. Causal power is at the heart of critical realist philosophy of science. Like Ragin, critical realism suggests empirical analysis as merely describing underlying causal relationships. Empirical statements must be substantively interpreted into causal claims. The article is critical of “empiricist” QCA that infers causality from the robustness of set relationships.
{"title":"Uncertainty, Possibility, and Causal Power in QCA","authors":"R. Rutten","doi":"10.1177/00491241211031268","DOIUrl":"https://doi.org/10.1177/00491241211031268","url":null,"abstract":"Uncertainty undermines causal claims; however, the nature of causal claims decides what counts as relevant uncertainty. Empirical robustness is imperative in regularity theories of causality. Regularity theory features strongly in QCA, making its case sensitivity a weakness. Following qualitative comparative analysis (QCA) founder Charles Ragin’s emphasis on ontological realism, this article suggests causality as a power and thus breaks with the ontological determinism of regularity theories. Exercising causal powers makes it possible for human agents to achieve an outcome but does not determine that they will. The article explains how QCA’s truth table analysis “models” possibilistic uncertainty and how crisp sets do this better than fuzzy sets. Causal power is at the heart of critical realist philosophy of science. Like Ragin, critical realism suggests empirical analysis as merely describing underlying causal relationships. Empirical statements must be substantively interpreted into causal claims. The article is critical of “empiricist” QCA that infers causality from the robustness of set relationships.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/00491241211031268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45443051","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 : 2021-07-21DOI: 10.1177/00491241211031271
C. Neuert, Katharina Meitinger, Dorothée Behr
The method of web probing integrates cognitive interviewing techniques into web surveys and is increasingly used to evaluate survey questions. In a usual web probing scenario, probes are administered immediately after the question to be tested (concurrent probing), typically as open-ended questions. A second possibility of administering probes is in a closed format, whereby the response categories for the closed probes are developed during previously conducted qualitative cognitive interviews. Using closed probes has several benefits, such as reduced costs and time efficiency, because this method does not require manual coding of open-ended responses. In this article, we investigate whether the insights gained into item functioning when implementing closed probes are comparable to the insights gained when asking open-ended probes and whether closed probes are equally suitable to capture the cognitive processes for which traditionally open-ended probes are intended. The findings reveal statistically significant differences with regard to the variety of themes, the patterns of interpretation, the number of themes per respondent, and nonresponse. No differences in number of themes across formats by sex and educational level were found.
{"title":"Open-ended versus Closed Probes: Assessing Different Formats of Web Probing","authors":"C. Neuert, Katharina Meitinger, Dorothée Behr","doi":"10.1177/00491241211031271","DOIUrl":"https://doi.org/10.1177/00491241211031271","url":null,"abstract":"The method of web probing integrates cognitive interviewing techniques into web surveys and is increasingly used to evaluate survey questions. In a usual web probing scenario, probes are administered immediately after the question to be tested (concurrent probing), typically as open-ended questions. A second possibility of administering probes is in a closed format, whereby the response categories for the closed probes are developed during previously conducted qualitative cognitive interviews. Using closed probes has several benefits, such as reduced costs and time efficiency, because this method does not require manual coding of open-ended responses. In this article, we investigate whether the insights gained into item functioning when implementing closed probes are comparable to the insights gained when asking open-ended probes and whether closed probes are equally suitable to capture the cognitive processes for which traditionally open-ended probes are intended. The findings reveal statistically significant differences with regard to the variety of themes, the patterns of interpretation, the number of themes per respondent, and nonresponse. No differences in number of themes across formats by sex and educational level were found.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/00491241211031271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46997234","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 : 2021-07-02DOI: 10.1177/0049124120986208
M. Kalmijn
Virtually, all large-scale family surveys in the United States and Europe have yielded a positive view of family ties in contemporary societies. The present study examines whether surveys like these are affected by selective nonresponse. Are people with negative family ties less likely to participate in surveys, and if so, to what extent does this yield a biased descriptive view of family solidarity? Using a novel multiactor design with matched register data, we examine the determinants of nonresponse of the parents of adult children aged 25–45 in the Netherlands. Our analysis reveals significant effects of the strength of parent–child ties on parental nonresponse, especially for fathers. Moreover, we find negative effects of divorce on father’s participation and this effect is stronger when family ties are weak. While these findings support the hypothesis of selective nonresponse, the magnitude of the effects is small and descriptive findings on family ties change only modestly when correcting for selective nonresponse.
{"title":"Are National Family Surveys Biased toward the Happy Family? A Multiactor Analysis of Selective Survey Nonresponse","authors":"M. Kalmijn","doi":"10.1177/0049124120986208","DOIUrl":"https://doi.org/10.1177/0049124120986208","url":null,"abstract":"Virtually, all large-scale family surveys in the United States and Europe have yielded a positive view of family ties in contemporary societies. The present study examines whether surveys like these are affected by selective nonresponse. Are people with negative family ties less likely to participate in surveys, and if so, to what extent does this yield a biased descriptive view of family solidarity? Using a novel multiactor design with matched register data, we examine the determinants of nonresponse of the parents of adult children aged 25–45 in the Netherlands. Our analysis reveals significant effects of the strength of parent–child ties on parental nonresponse, especially for fathers. Moreover, we find negative effects of divorce on father’s participation and this effect is stronger when family ties are weak. While these findings support the hypothesis of selective nonresponse, the magnitude of the effects is small and descriptive findings on family ties change only modestly when correcting for selective nonresponse.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"561 - 586"},"PeriodicalIF":6.3,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0049124120986208","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44992601","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 : 2021-06-16DOI: 10.1177/00491241221091756
R. Fischer, J. Karl, Johnny Fontaine, Y. Poortinga
We comment on the argument by Welzel, Brunkert, Kruse and Inglehart (2021) that theoretically expected associations in nomological networks should take priority over invariance tests in cross-national research. We agree that narrow application of individual tools, such as multi-group confirmatory factor analysis with data that violates the assumptions of these techniques, can be misleading. However, findings that fit expectations of nomological networks may not be free of bias. We present supporting evidence of systematic bias affecting nomological network relationships from a) previous research on intelligence and response styles, b) two simulation studies, and c) data on the choice index from the World Value Survey (WVS). Our main point is that nomological network analysis by itself is insufficient to rule out systematic bias in data. We point out how a thoughtful exploration of sources of biases in cross-national data can contribute to stronger theory development.
{"title":"Evidence of Validity Does not Rule out Systematic Bias: A Commentary on Nomological Noise and Cross-Cultural Invariance","authors":"R. Fischer, J. Karl, Johnny Fontaine, Y. Poortinga","doi":"10.1177/00491241221091756","DOIUrl":"https://doi.org/10.1177/00491241221091756","url":null,"abstract":"We comment on the argument by Welzel, Brunkert, Kruse and Inglehart (2021) that theoretically expected associations in nomological networks should take priority over invariance tests in cross-national research. We agree that narrow application of individual tools, such as multi-group confirmatory factor analysis with data that violates the assumptions of these techniques, can be misleading. However, findings that fit expectations of nomological networks may not be free of bias. We present supporting evidence of systematic bias affecting nomological network relationships from a) previous research on intelligence and response styles, b) two simulation studies, and c) data on the choice index from the World Value Survey (WVS). Our main point is that nomological network analysis by itself is insufficient to rule out systematic bias in data. We point out how a thoughtful exploration of sources of biases in cross-national data can contribute to stronger theory development.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"1420 - 1437"},"PeriodicalIF":6.3,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42078224","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 : 2021-06-15DOI: 10.1177/00491241211024295
Weihua An
This special issue, “New Quantitative Approaches to Studying Social Inequality”, aims to present some of the latest methodological innovations that arise from new analytical methods, innovative study designs, and novel and large-scale data that are particularly useful for studying social inequality. The articles included in the special issue not only showcase methodological innovations but also share the common theme that social inequalities are often interconnected across domains of life, time, space, or different policies.
{"title":"Fear Not Scarcity but Inequality, Not Poverty but Instability","authors":"Weihua An","doi":"10.1177/00491241211024295","DOIUrl":"https://doi.org/10.1177/00491241211024295","url":null,"abstract":"This special issue, “New Quantitative Approaches to Studying Social Inequality”, aims to present some of the latest methodological innovations that arise from new analytical methods, innovative study designs, and novel and large-scale data that are particularly useful for studying social inequality. The articles included in the special issue not only showcase methodological innovations but also share the common theme that social inequalities are often interconnected across domains of life, time, space, or different policies.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"50 1","pages":"939 - 943"},"PeriodicalIF":6.3,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/00491241211024295","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42687337","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 : 2021-06-03DOI: 10.1177/0049124121995554
Michael Baumgartner, Mathias Ambühl
Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the optimally obtainable consistency and coverage scores for data δ , so far, is a matter of repeatedly applying CCMs to δ while varying threshold settings. This article introduces a procedure called ConCovOpt that calculates, prior to actual CCM analyses, the consistency and coverage scores that can optimally be obtained by models inferred from δ . Moreover, we show how models reaching optimal scores can be methodically built in case of crisp-set and multi-value data. ConCovOpt is a tool, not for blindly maximizing model fit, but for rendering transparent the space of viable models at optimal fit scores in order to facilitate informed model selection—which, as we demonstrate by various data examples, may have substantive modeling implications.
{"title":"Optimizing Consistency and Coverage in Configurational Causal Modeling","authors":"Michael Baumgartner, Mathias Ambühl","doi":"10.1177/0049124121995554","DOIUrl":"https://doi.org/10.1177/0049124121995554","url":null,"abstract":"Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the optimally obtainable consistency and coverage scores for data δ , so far, is a matter of repeatedly applying CCMs to δ while varying threshold settings. This article introduces a procedure called ConCovOpt that calculates, prior to actual CCM analyses, the consistency and coverage scores that can optimally be obtained by models inferred from δ . Moreover, we show how models reaching optimal scores can be methodically built in case of crisp-set and multi-value data. ConCovOpt is a tool, not for blindly maximizing model fit, but for rendering transparent the space of viable models at optimal fit scores in order to facilitate informed model selection—which, as we demonstrate by various data examples, may have substantive modeling implications.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"1288 - 1320"},"PeriodicalIF":6.3,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0049124121995554","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46505370","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 : 2021-05-28DOI: 10.1177/00491241211014237
Linda Zhao, F. Garip
Network externalities (where the value of a practice is a function of network alters that have already adopted the practice) are mechanisms that exacerbate social inequality under the condition of homophily (where advantaged individuals poised to be primary adopters are socially connected to other advantaged individuals). In their 2011 article, Dimaggio and Garip use an agent-based model of diffusion on a real-life population for empirical illustration and, thus, do not consider consolidation (correlation between traits), a population parameter that shapes network structure and diffusion. Using an agent-based model, this article shows that prior findings linking homophily to segregated social ties and to differential diffusion outcomes are contingent on high levels of consolidation. Homophily, under low consolidation, is not sufficient to exacerbate existing differences in adoption probabilities across groups and can even end up alleviating intergroup inequality by facilitating diffusion.
{"title":"Network Diffusion Under Homophily and Consolidation as a Mechanism for Social Inequality","authors":"Linda Zhao, F. Garip","doi":"10.1177/00491241211014237","DOIUrl":"https://doi.org/10.1177/00491241211014237","url":null,"abstract":"Network externalities (where the value of a practice is a function of network alters that have already adopted the practice) are mechanisms that exacerbate social inequality under the condition of homophily (where advantaged individuals poised to be primary adopters are socially connected to other advantaged individuals). In their 2011 article, Dimaggio and Garip use an agent-based model of diffusion on a real-life population for empirical illustration and, thus, do not consider consolidation (correlation between traits), a population parameter that shapes network structure and diffusion. Using an agent-based model, this article shows that prior findings linking homophily to segregated social ties and to differential diffusion outcomes are contingent on high levels of consolidation. Homophily, under low consolidation, is not sufficient to exacerbate existing differences in adoption probabilities across groups and can even end up alleviating intergroup inequality by facilitating diffusion.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"50 1","pages":"1150 - 1185"},"PeriodicalIF":6.3,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/00491241211014237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43568403","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 : 2021-05-20DOI: 10.1177/0049124120986203
Oluwaseun L. Olanipekun, JuLong Zhao, Rongdong Wang, Stephen A.Sedory, Sarjinder Singh
In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing sensitive characteristics. However, there is a paucity of research studies that have addressed higher order interactions between these sensitive characters. In this article, we develop a new theory based on three proposed randomized response models which we name as: simple model, semi-crossed model, and fully crossed model. Twenty-one new unbiased estimators of seven parameters are introduced, their variance expressions are derived, and unbiased estimators of variances are developed. The three models are compared under various values of the parameters by computing the percent relative efficiency of one model over another model. The most efficient model is then applied to study the population proportions of three varieties of smoking habits among students, and their first- and second-order interactions. The last four sections (Ninth to Twelfth) are verifications of theoretical results using the Cramer–Rao lower bounds of variances for the developed 21 new estimators in randomized response sampling.
{"title":"A Theory of Higher Order Interactions Between Sensitive Variables: Empirical Evidences and an Application to a Variety of Smoking","authors":"Oluwaseun L. Olanipekun, JuLong Zhao, Rongdong Wang, Stephen A.Sedory, Sarjinder Singh","doi":"10.1177/0049124120986203","DOIUrl":"https://doi.org/10.1177/0049124120986203","url":null,"abstract":"In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing sensitive characteristics. However, there is a paucity of research studies that have addressed higher order interactions between these sensitive characters. In this article, we develop a new theory based on three proposed randomized response models which we name as: simple model, semi-crossed model, and fully crossed model. Twenty-one new unbiased estimators of seven parameters are introduced, their variance expressions are derived, and unbiased estimators of variances are developed. The three models are compared under various values of the parameters by computing the percent relative efficiency of one model over another model. The most efficient model is then applied to study the population proportions of three varieties of smoking habits among students, and their first- and second-order interactions. The last four sections (Ninth to Twelfth) are verifications of theoretical results using the Cramer–Rao lower bounds of variances for the developed 21 new estimators in randomized response sampling.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"52 1","pages":"642 - 763"},"PeriodicalIF":6.3,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0049124120986203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42929678","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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