Disease Mapping with WinBUGS and MLwiN / Statistics in Practice (PDF)
(Sprache: Englisch)
Disease mapping involves the analysis of geo-referenced disease
incidence data and has many applications, for example within
resource allocation, cluster alarm analysis, and ecological
studies. There is a real need amongst public health workers...
incidence data and has many applications, for example within
resource allocation, cluster alarm analysis, and ecological
studies. There is a real need amongst public health workers...
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Disease mapping involves the analysis of geo-referenced disease
incidence data and has many applications, for example within
resource allocation, cluster alarm analysis, and ecological
studies. There is a real need amongst public health workers for
simpler and more efficient tools for the analysis of geo-referenced
disease incidence data. Bayesian and multilevel methods provide the
required efficiency, and with the emergence of software packages
- such as WinBUGS and MLwiN - are now easy to implement
in practice.
* Provides an introduction to Bayesian and multilevel modelling
in disease mapping.
* Adopts a practical approach, with many detailed worked
examples.
* Includes introductory material on WinBUGS and MLwiN.
* Discusses three applications in detail - relative risk
estimation, focused clustering, and ecological analysis.
* Suitable for public health workers and epidemiologists with a
sound statistical knowledge.
* Supported by a Website featuring data sets and WinBUGS and
MLwiN programs.
Disease Mapping with WinBUGS and MLwiN provides a
practical introduction to the use of software for disease mapping
for researchers, practitioners and graduate students from
statistics, public health and epidemiology who analyse disease
incidence data.
incidence data and has many applications, for example within
resource allocation, cluster alarm analysis, and ecological
studies. There is a real need amongst public health workers for
simpler and more efficient tools for the analysis of geo-referenced
disease incidence data. Bayesian and multilevel methods provide the
required efficiency, and with the emergence of software packages
- such as WinBUGS and MLwiN - are now easy to implement
in practice.
* Provides an introduction to Bayesian and multilevel modelling
in disease mapping.
* Adopts a practical approach, with many detailed worked
examples.
* Includes introductory material on WinBUGS and MLwiN.
* Discusses three applications in detail - relative risk
estimation, focused clustering, and ecological analysis.
* Suitable for public health workers and epidemiologists with a
sound statistical knowledge.
* Supported by a Website featuring data sets and WinBUGS and
MLwiN programs.
Disease Mapping with WinBUGS and MLwiN provides a
practical introduction to the use of software for disease mapping
for researchers, practitioners and graduate students from
statistics, public health and epidemiology who analyse disease
incidence data.
Autoren-Porträt von Andrew B. Lawson, William J. Browne, Carmen L. Vidal Rodeiro
Andrew B. Lawson is a professor of biostatistics and eminent scholar in the Division of Biostatistics and Epidemiology in the College of Medicine at the Medical University of South Carolina. He is an ASA fellow and an advisor in disease mapping and risk assessment for the World Health Organization. Dr. Lawson has published over 100 journal papers and eight books and is the founding editor of Spatial and Spatio-temporal Epidemiology. He received a PhD in spatial statistics from the University of St. Andrews. His research interests include the analysis of clustered disease maps, spatial and spatio-temporal disease surveillance, nutritional measurement error, and Bayesian latent variable and SEM modeling.
Bibliographische Angaben
- Autoren: Andrew B. Lawson , William J. Browne , Carmen L. Vidal Rodeiro
- 2003, 292 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 047085605X
- ISBN-13: 9780470856055
- Erscheinungsdatum: 09.09.2003
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- Größe: 10 MB
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Sprache:
Englisch
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