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                            Activity Number:
                            
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                            354 
                            	- SPEED: Big Data, Small Area Estimation, and Methodological Innovations Under Development, Part 2
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                            Type:
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                            Contributed
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                            Date/Time:
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                            Tuesday, July 30, 2019 : 10:30 AM to 11:15 AM
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                            Sponsor:
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                            Survey Research Methods Section
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                            Abstract #307748
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                            Title:
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                            Small Area Estimation on Fatalistic Beliefs About Cancer Using the Health Information National Trends Survey
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                        Author(s):
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                        Benmei Liu* and Elise Rice and Richard Moser 
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                        Companies:
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                        National Cancer Institute and National Institute of Dental and Craniofacial Research and National Cancer Institute 
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                        Keywords:
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                            cancer fatalistic beliefs; 
                            Model-based estimates; 
                            MCMC; 
                            model validation; 
                            mapping 
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                        Abstract:
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                            GIS maps using the Health Information National Trends Survey (HINTS) data can provide a visual representation of possible geographic relationships in HINTS cancer-related knowledge variables. However, due to instability in some state values from relatively small sample sizes, the GIS maps that have been developed cannot provide specific state-level or county-level estimates of HINTS variables. Rather, they can mainly illustrate regional differences. The goal of this research is to develop model-based methodology through small area estimation (SAE) techniques to produce state- and county-level estimates on several outcomes related to fatalistic beliefs about cancer. Both area-level and unit-level models are explored. This paper describes the methodology used and presents the results.   
                         
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                    Authors who are presenting talks have a * after their name.