List experiments are a widely used survey technique for estimating the prevalence of socially sensitive attitudes or behaviors. Their design, however, makes them vulnerable to bias: because treatment group respondents see a greater number of items (J+1) than control group respondents (J), the treatment group mean may be mechanically inflated due simply to the greater number of items. The few previous studies that directly examine this do not arrive at definitive conclusions. We find clear evidence of inflation in an original dataset, though only among respondents with low educational attainment. Furthermore, we use available data from previous studies and find similar heterogeneous patterns. The evidence of heterogeneous effects has implications for the interpretation of previous research using list experiments, especially in developing world contexts. We recommend a simple solution: using a necessarily false placebo statement for the control group equalizes list lengths, thereby protecting against mechanical inflation without imposing costs or altering interpretations.
{"title":"Placebo Statements in List Experiments","authors":"Guillem Riambau, Kai Ostwald","doi":"10.2139/ssrn.3394417","DOIUrl":"https://doi.org/10.2139/ssrn.3394417","url":null,"abstract":"List experiments are a widely used survey technique for estimating the prevalence of socially sensitive attitudes or behaviors. Their design, however, makes them vulnerable to bias: because treatment group respondents see a greater number of items (J+1) than control group respondents (J), the treatment group mean may be mechanically inflated due simply to the greater number of items. The few previous studies that directly examine this do not arrive at definitive conclusions. We find clear evidence of inflation in an original dataset, though only among respondents with low educational attainment. Furthermore, we use available data from previous studies and find similar heterogeneous patterns. The evidence of heterogeneous effects has implications for the interpretation of previous research using list experiments, especially in developing world contexts. We recommend a simple solution: using a necessarily false placebo statement for the control group equalizes list lengths, thereby protecting against mechanical inflation without imposing costs or altering interpretations.","PeriodicalId":414104,"journal":{"name":"AARN: Research Methods (Sub-Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122401320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Do Americans spend more time watching TV and shopping than do Britons? If so, then where does the additional time come from? In this study, we present evidence that aggregate time-use comparisons are potentially misleading, because they ignore differences in sample and population composition that directly affect how people plan their daily lives. These aggregate comparisons are also potentially misleading because they do not take into account the highly censored and sparse nature of time-use data as well as the fact that we all work on the same budget of 1440 minutes each day. For these reasons, we propose a framework for time-use analysis that provides insights into how demography and geography affect the value people assign to time spent on the various activities of daily life, while taking into account the unique features of time-use data. We use this framework to compare how Americans and Britons differ in their time-use, after accounting for other demographic and geographic factors affecting the value of time.
{"title":"A New Framework for Time-Use Analysis","authors":"W. Kamakura","doi":"10.2139/ssrn.2161942","DOIUrl":"https://doi.org/10.2139/ssrn.2161942","url":null,"abstract":"Do Americans spend more time watching TV and shopping than do Britons? If so, then where does the additional time come from? In this study, we present evidence that aggregate time-use comparisons are potentially misleading, because they ignore differences in sample and population composition that directly affect how people plan their daily lives. These aggregate comparisons are also potentially misleading because they do not take into account the highly censored and sparse nature of time-use data as well as the fact that we all work on the same budget of 1440 minutes each day. For these reasons, we propose a framework for time-use analysis that provides insights into how demography and geography affect the value people assign to time spent on the various activities of daily life, while taking into account the unique features of time-use data. We use this framework to compare how Americans and Britons differ in their time-use, after accounting for other demographic and geographic factors affecting the value of time.","PeriodicalId":414104,"journal":{"name":"AARN: Research Methods (Sub-Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131988403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Defining and measuring concepts accurately is essential for good social science research. Giovanni Sartori's views about concepts in Social Science had invited wide attention from social scientists during 1990s. Dr. Sethu Madhavan Puravangara critically reviews the the concept analysis methodology proposed by Giovanni Sartori in this paper. This paper analyses logical steps proposed by Giovanni Sartori in moving from conceptualization to measurement and the relationships among meanings, terms and observations.
{"title":"Concept Analysis: A Critical Appraisal","authors":"Sethu Madhavan Puravangara","doi":"10.2139/SSRN.2372524","DOIUrl":"https://doi.org/10.2139/SSRN.2372524","url":null,"abstract":"Defining and measuring concepts accurately is essential for good social science research. Giovanni Sartori's views about concepts in Social Science had invited wide attention from social scientists during 1990s. Dr. Sethu Madhavan Puravangara critically reviews the the concept analysis methodology proposed by Giovanni Sartori in this paper. This paper analyses logical steps proposed by Giovanni Sartori in moving from conceptualization to measurement and the relationships among meanings, terms and observations.","PeriodicalId":414104,"journal":{"name":"AARN: Research Methods (Sub-Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127685489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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