Disease Mapping with WinBUGS and MLwiN (eBook)

Andrew B. Lawson, William J. Browne, Carmen L. Vidal Rodeiro (Autoren)

eBook Download: PDF

2003
292 Seiten
John Wiley & Sons (Verlag)
978-0-470-85605-5 (ISBN)

Infos

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.

Autor

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.

Inhalt

Preface.

Notation.

0.1 Standard notation for multilevel modelling.

0.2 Spatial multiple-membership models and the MMMC
notation.

0.3 Standard notation for WinBUGS models.

1. Disease mapping basics.

1.1 Disease mapping and map reconstruction.

1.2 Disease map restoration.

2. Bayesian hierarchical modelling.

2.1 Likelihood and posterior distributions.

2.2 Hierarchical models.

2.3 Posterior inference.

2.4 Markov chain Monte Carlo methods.

2.5 Metropolis and Metropolis-Hastings algorithms.

2.6 Residuals and goodness of fit.

3. Multilevel modelling.

3.1 Continuous response models.

3.2 Estimation procedures for multilevel models.

3.3 Poisson response models.

3.4 Incorporating spatial information.

3.5 Discussion.

4. WinBUGS basics.

4.1 About WinBUGS.

4.2 Start using WinBUGS.

4.3 Specification of the model.

4.4 Model fitting.

4.5 Scripts.

4.6 Checking convergence.

4.7 Spatial modelling: GeoBUGS.

4 .8 Conclusions.

5. MLwiN basics.

5.1 About MLwiN.

5.2 Getting started.

5.3 Fitting statistical models.

5.4 MCMC estimation in MLwiN.

5.5 Spatial modelling.

5.6 Conclusions.

6. Relative risk estimation.

6.1 Relative risk estimation using WinBUGS.

6.2 Spatial prediction.

6.3 An analysis of the Ohio dataset using MLwiN.

7. Focused clustering: the analysis of putative health
hazards.

7.1 Introduction.

7.2 Study design.

7.3 Problems of inference.

7.4 Modelling the hazard exposure risk.

7.5 Models for count data.

7.6 Bayesian models.

7.7 Focused clustering in WinBUGS.

7.8 Focused clustering in MLwiN.

8. Ecological analysis.

8.1 Introduction.

8.2 Statistical models.

8.3 WinBUGS analyses of ecological datasets.

8.4 MLwiN analyses of ecological datasets.

9. Spatially-correlated survival analysis.

9.1 Survival analysis in WinBUGS.

9.2 Survival analysis in MLwiN.

10. Epilogue.

Appendix 1: WinBUGS code for focused clustering models.

A.1: Falkirk example.

A.2: Ohio example.

Appendix 2: S-Plus function for conversion to GeoBUGS
format.

Bibliography.

Index.

Rezensionen

"...written at a level that will be readily accessible to
anyone with a modest background in applied statistics."
(Technometrics, February 2005)

"The book certainly is a nice addition to my disease mapping
books. The book is equally useful for the undergraduate and
graduate students as well as public health professionals.
(E-STREAMS, July 2004)

"...a good guide and a useful addition for any
graduate statistician or epidemiologist..."
(Statistical Methods in Medical Research, No.13 2004)

"...outlines the models used in statistical disease mapping, and
gives details of how the models can be implemented using two
packages..." (Short Book Reviews, Vol.24, No.3)

"Readers... will greatly profit from this book"
(International Society of Clinical Biostatistics Dec
2005)

Produkt-Details

• Erscheint lt. Verlag: 31.10.2003
• Reihe/Serie: Statistics in Practice
• Reihe/Serie: Statistics in Practice
• Sprache: englisch
• Themenwelt: Informatik ► Office Programme ► Outlook
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Studium ► Querschnittsbereiche ► Prävention / Gesundheitsförderung
• Themenwelt: Technik
• Schlagworte: Biostatistics • Biostatistik • Gesundheits- u. Sozialwesen • Health & Social Care • Health Care Administration • Statistics • Statistik • Verwaltung im Gesundheitswesen
• ISBN-10: 0-470-85605-X / 047085605X
• ISBN-13: 978-0-470-85605-5 / 9780470856055