Bayesian Models to Generate Small Area Estimates of Population Health: Tutorial for Using Rate Stabilizing Tools and Their Output
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- Title
- Bayesian Models to Generate Small Area Estimates of Population Health: Tutorial for Using Rate Stabilizing Tools and Their Output
- Creators
- David DeLara (Corresponding Author) - National Center for Chronic Disease Prevention and Health PromotionRyan Zomorrodi - University of Illinois ChicagoHarrison Quick - University of MinnesotaJoshua Tootoo - University of Illinois ChicagoRuiyang Li - University of Illinois ChicagoJustan Baker - Rhode Island Department of HealthJihyeon Kwon - Drexel UniversityMichele Casper - National Center for Chronic Disease Prevention and Health PromotionAdam Vaughan - National Center for Chronic Disease Prevention and Health Promotion
- Publication Details
- JMIR public health and surveillance, v 12, e83498
- Publisher
- Jmir Publications, Inc
- Number of pages
- 17
- Grant note
- The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and PreventionU.S. Department of Health and Human Services
Acknowledgments This research uses data from the North Carolina Center for Health Statistics (SCHS) to illustrate the use of the RSTbx. The authors wish to acknowledge SCHS but are responsible for the analysis and interpretation of these data. The authors attest that there was no use of generative artificial intelligence (AI) technology in the generation of text, figures, or other informational content of this manuscript. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Department of Health and Human Services
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:001682085800001
- Other Identifier
- 991022156300304721