On the clustering term in ecological analysis: how do different prior specifications affect results?
Author
Abstract
Suggested Citation
DOI: 10.1007/s10260-007-0089-x
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Kelsall J. & Eld J.W., 2002. "Modeling Spatial Variation in Disease Risk: A Geostatistical Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 692-701, September.
- Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
- Green P.J. & Richardson S., 2002. "Hidden Markov Models and Disease Mapping," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1055-1070, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Mahdi Hosseinpouri & Majid Jafari Khaledi, 2019. "An area-specific stick breaking process for spatial data," Statistical Papers, Springer, vol. 60(1), pages 199-221, February.
- Mohammadreza Mohebbi & Rory Wolfe & Andrew Forbes, 2014. "Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach," IJERPH, MDPI, vol. 11(1), pages 1-20, January.
- Hong-Ding Yang & Yun-Huan Lee & Che-Yang Lin, 2023. "On Study of the Occurrence of Earth-Size Planets in Kepler Mission Using Spatial Poisson Model," Mathematics, MDPI, vol. 11(11), pages 1-14, May.
- Ugarte, M.D. & Goicoa, T. & Militino, A.F., 2009. "Empirical Bayes and Fully Bayes procedures to detect high-risk areas in disease mapping," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2938-2949, June.
- Vidal Rodeiro, Carmen L. & Lawson, Andrew B., 2005. "An evaluation of the edge effects in disease map modelling," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 45-62, April.
- Zhang Hongmei & Gan Jianjun, 2012. "A Reproducing Kernel-Based Spatial Model in Poisson Regressions," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-26, October.
- Lee, Dae-Jin & Durbán, María, 2008. "Smooth-car mixed models for spatial count data," DES - Working Papers. Statistics and Econometrics. WS ws085820, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Lee, Dae-Jin & Durbán, María, 2009. "Smooth-CAR mixed models for spatial count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2968-2979, June.
- Miklos Arato, N. & Dryden, Ian L. & Taylor, Charles C., 2006. "Hierarchical Bayesian modelling of spatial age-dependent mortality," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1347-1363, November.
- Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
- Zhang, Tonglin & Lin, Ge, 2016. "On Moran’s I coefficient under heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 83-94.
- Lee, Dae-Jin & Ayma Anza, Diego Armando & Durbán, María & Eilers, Paul, 2015. "Penalized composite link mixed models for two-dimensional count data," DES - Working Papers. Statistics and Econometrics. WS ws1509, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Wang, Craig & Furrer, Reinhard, 2021. "Combining heterogeneous spatial datasets with process-based spatial fusion models: A unifying framework," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
- Katherine Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
- Eibich, Peter & Ziebarth, Nicolas, 2014.
"Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models,"
EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
- Eibich, Peter & Ziebarth, Nicolas R., 2014. "Examining the structure of spatial health effects in Germany using Hierarchical Bayes Models," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 305-320.
- Eibich, Peter & Ziebarth, Nicolas, 2013. "Examining the Structure of Spatial Health Effects using Hierarchical Bayes Models," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79844, Verein für Socialpolitik / German Economic Association.
- Peter Eibich & Nicolas R. Ziebarth, 2013. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," SOEPpapers on Multidisciplinary Panel Data Research 620, DIW Berlin, The German Socio-Economic Panel (SOEP).
- Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
- Spezia, L. & Cooksley, S.L. & Brewer, M.J. & Donnelly, D. & Tree, A., 2014. "Modelling species abundance in a river by Negative Binomial hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 599-614.
- Zhengyi Zhou & David S. Matteson & Dawn B. Woodard & Shane G. Henderson & Athanasios C. Micheas, 2015. "A Spatio-Temporal Point Process Model for Ambulance Demand," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 6-15, March.
- Eric C. Tassone & Marie Lynn Miranda & Alan E. Gelfand, 2010. "Disaggregated spatial modelling for areal unit categorical data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 175-190, January.
- Junming Li & Xiulan Han & Xiao Li & Jianping Yang & Xuejiao Li, 2018. "Spatiotemporal Patterns of Ground Monitored PM 2.5 Concentrations in China in Recent Years," IJERPH, MDPI, vol. 15(1), pages 1-15, January.
More about this item
Keywords
Hierarchical Bayesian model; Ecological analysis; Geographical epidemiology; Sensitivity analysis; Clustering;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stmapp:v:18:y:2009:i:1:p:49-61. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.