Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model
Over the past eight decades, millions of people have been surveyed on their political opinions. Until recently, however, polls rarely included enough questions in a given domain to apply scaling techniques such as IRT models at the individual level, preventing scholars from taking full advantage of...
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| Format: | Article |
| Language: | en_US |
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Oxford University Press
2017
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| Online Access: | http://hdl.handle.net/1721.1/106583 https://orcid.org/0000-0002-6769-1438 https://orcid.org/0000-0003-4716-2106 |
| _version_ | 1826212748972785664 |
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| author | Caughey, Devin Warshaw, Christopher S |
| author2 | Massachusetts Institute of Technology. Department of Political Science |
| author_facet | Massachusetts Institute of Technology. Department of Political Science Caughey, Devin Warshaw, Christopher S |
| author_sort | Caughey, Devin |
| collection | MIT |
| description | Over the past eight decades, millions of people have been surveyed on their political opinions. Until recently, however, polls rarely included enough questions in a given domain to apply scaling techniques such as IRT models at the individual level, preventing scholars from taking full advantage of historical survey data. To address this problem, we develop a Bayesian group-level IRT approach that models latent traits at the level of demographic and/or geographic groups rather than individuals. We use a hierarchical model to borrow strength cross-sectionally and dynamic linear models to do so across time. The group-level estimates can be weighted to generate estimates for geographic units. This framework opens up vast new areas of research on historical public opinion, especially at the subnational level. We illustrate this potential by estimating the average policy liberalism of citizens in each U.S. state in each year between 1972 and 2012. |
| first_indexed | 2024-09-23T15:37:17Z |
| format | Article |
| id | mit-1721.1/106583 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:37:17Z |
| publishDate | 2017 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | mit-1721.1/1065832022-09-29T15:05:09Z Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model Caughey, Devin Warshaw, Christopher S Massachusetts Institute of Technology. Department of Political Science Caughey, Devin Warshaw, Christopher S Over the past eight decades, millions of people have been surveyed on their political opinions. Until recently, however, polls rarely included enough questions in a given domain to apply scaling techniques such as IRT models at the individual level, preventing scholars from taking full advantage of historical survey data. To address this problem, we develop a Bayesian group-level IRT approach that models latent traits at the level of demographic and/or geographic groups rather than individuals. We use a hierarchical model to borrow strength cross-sectionally and dynamic linear models to do so across time. The group-level estimates can be weighted to generate estimates for geographic units. This framework opens up vast new areas of research on historical public opinion, especially at the subnational level. We illustrate this potential by estimating the average policy liberalism of citizens in each U.S. state in each year between 1972 and 2012. Massachusetts Institute of Technology. School of Humanities, Arts, and Social Sciences 2017-01-23T16:38:50Z 2017-01-23T16:38:50Z 2015-02 Article http://purl.org/eprint/type/JournalArticle 1047-1987 1476-4989 http://hdl.handle.net/1721.1/106583 Caughey, D., and C. Warshaw. “Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model.” Political Analysis 23.2 (2015): 197–211. https://orcid.org/0000-0002-6769-1438 https://orcid.org/0000-0003-4716-2106 en_US http://dx.doi.org/10.1093/pan/mpu021 Political Analysis Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Oxford University Press MIT Web Domain |
| spellingShingle | Caughey, Devin Warshaw, Christopher S Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title | Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title_full | Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title_fullStr | Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title_full_unstemmed | Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title_short | Dynamic Estimation of Latent Opinion Using a Hierarchical Group-Level IRT Model |
| title_sort | dynamic estimation of latent opinion using a hierarchical group level irt model |
| url | http://hdl.handle.net/1721.1/106583 https://orcid.org/0000-0002-6769-1438 https://orcid.org/0000-0003-4716-2106 |
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