Cross-survey analysis to estimate low incidence religious groups

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Show simple item record Tighe, Elizabeth Livert, David Barnett, Melissa Saxe, Leonard 2017-08-21T17:10:48Z 2017-08-21T17:10:48Z 2010-06-16
dc.identifier.citation Sociological Methods & Research (2010) 39, 1: 56 - 82
dc.identifier.issn 1552-8294
dc.description.abstract Population-based surveys are of limited utility to estimate rare or low-incidence groups, particularly for those defined by religion or ethnicity not included in the U.S. Census. Methods of cross-survey analysis and small area estimation, however, can be used to provide reliable estimates of such low-incidence groups. To illustrate these methods, data from 50 national surveys are combined to examine the Jewish population in the United States. Hierarchical models are used to examine clustering of respondents within surveys and geographic regions. Bayesian analyses with Monte Carlo simulations are used to obtain pooled, state-level estimates poststratified by sex, race, education, and age to obtain certainty intervals about the estimates. This cross-survey approach provides a useful and practical analytic framework that can be generalized both to more extensive study of religion in the United States and to other social science problems in which single data sources are insufficient for reliable statistical inference. Open Access Sociological Methods & Research (2010) 39, 1: 56 - 82
dc.language English
dc.language.iso en
dc.publisher SAGE Publications
dc.rights (c) 2010 Tighe, Livert, Barnett, Saxe
dc.subject Census
dc.subject Cross-Survey
dc.subject Jewish Population
dc.title Cross-survey analysis to estimate low incidence religious groups
dc.type Article
dc.identifier.doi 2010
dc.description.esploro Y
mods.esploro Y

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