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Biblioteca

MARC Lista (tabellare)
Bayesian biostatistics [[electronic resource] /] / Emmanuel Lesaffre, Andrew B. Lawson
Bayesian biostatistics [[electronic resource] /] / Emmanuel Lesaffre, Andrew B. Lawson
Autore Lesaffre Emmanuel
Pubbl/distr/stampa Chichester, West Sussex, : John Wiley & Sons, 2012
Descrizione fisica 1 online resource (536 pages)
Disciplina 570.1/5195
Altri autori (Persone) LawsonAndrew (Andrew B.)
Collana Statistics in practice
Soggetto topico Biometry - Methodology
Bayesian statistical decision theory
ISBN 1-118-31457-3
1-280-77255-7
9786613683328
1-118-31456-5
1-119-94241-1
1-119-94240-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Basic concepts in Bayesian methods -- Bayes theorem -- Posterior summary measures -- More than one parameter -- The prior distribution -- Markov chain Monte Carlo -- Software -- Hierarchical models -- Model building and assessment -- Variable selection -- Bioassay -- Measurement error -- Survival analysis -- Longitudinal analysis -- Disease mapping & image analysis -- Final chapter -- Distributions.
Record Nr. UNINA-9910141259403321
Lesaffre Emmanuel  
Chichester, West Sussex, : John Wiley & Sons, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian biostatistics / / Emmanuel Lesaffre, Andrew B. Lawson
Bayesian biostatistics / / Emmanuel Lesaffre, Andrew B. Lawson
Autore Lesaffre Emmanuel
Edizione [1st ed.]
Pubbl/distr/stampa Chichester, West Sussex, : John Wiley & Sons, 2012
Descrizione fisica 1 online resource (536 pages)
Disciplina 570.1/5195
Altri autori (Persone) LawsonAndrew (Andrew B.)
Collana Statistics in practice
Soggetto topico Biometry - Methodology
Bayesian statistical decision theory
ISBN 1-118-31457-3
1-280-77255-7
9786613683328
1-118-31456-5
1-119-94241-1
1-119-94240-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Basic concepts in Bayesian methods -- Bayes theorem -- Posterior summary measures -- More than one parameter -- The prior distribution -- Markov chain Monte Carlo -- Software -- Hierarchical models -- Model building and assessment -- Variable selection -- Bioassay -- Measurement error -- Survival analysis -- Longitudinal analysis -- Disease mapping & image analysis -- Final chapter -- Distributions.
Record Nr. UNINA-9910807325103321
Lesaffre Emmanuel  
Chichester, West Sussex, : John Wiley & Sons, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Spatial and syndromic surveillance for public health [[electronic resource] /] / edited by Andrew B. Lawson, Ken Kleinman
Spatial and syndromic surveillance for public health [[electronic resource] /] / edited by Andrew B. Lawson, Ken Kleinman
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Descrizione fisica 1 online resource (285 p.)
Disciplina 614.4
Altri autori (Persone) LawsonAndrew (Andrew B.)
KleinmanKen
Soggetto topico Public health surveillance
Epidemiology
Soggetto genere / forma Electronic books.
ISBN 1-280-23853-4
9786610238538
0-470-09250-5
0-470-09249-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Spatial and Syndromic Surveillance for Public Health; Contents; Preface; List of Contributors; 1 Introduction: Spatial and syndromic surveillance for public health; 1.1 What is public health surveillance?; 1.1.1 Spatial surveillance; 1.1.2 Syndromic surveillance; 1.2 The increased importance of public health surveillance; 1.3 Geographic information, cluster detection and spatial surveillance; 1.4 Surveillance and screening; 1.5 Overview of process control and mapping; 1.5.1 Process control methodology; 1.5.2 The analysis of maps and surveillance; 1.6 The purpose of this book
1.6.1 Statistical surveillance and methodological development in a public health context1.6.2 The statistician's role in surveillance; 1.7 The contents of this book; Part I Introduction to Temporal Surveillance; 2 Overview of temporal surveillance; 2.1 Introduction; 2.1.1 Surveillance systems; 2.1.2 Surveillance attributes; 2.1.3 Early detection of unusual health events; 2.2 Statistical methods; 2.2.1 Historical limits method; 2.2.2 Process control charts; 2.2.3 Time-series analysis; 2.3 Conclusion; 3 Optimal surveillance; 3.1 Introduction
3.2 Optimality for a fixed sample and for on-line surveillance3.3 Specification of the statistical surveillance problem; 3.4 Evaluations of systems for surveillance; 3.4.1 Measures for a fixed sample situation adopted for surveillance; 3.4.2 False alarms; 3.4.3 Delay of the alarm; 3.4.4 Predictive value; 3.5 Optimality criteria; 3.5.1 Minimal expected delay; 3.5.2 Minimax optimality; 3.5.3 Average run length; 3.6 Optimality of some standard methods; 3.6.1 The likelihood ratio method; 3.6.2 The Shewhart method; 3.6.3 The CUSUM method; 3.6.4 Moving average and window-based methods
3.6.5 Exponentially weighted moving average methods3.7 Special aspects of optimality for surveillance of public health; 3.7.1 Gradual changes during outbreaks of diseases; 3.7.2 Change between unknown incidences; 3.7.3 Spatial and other multivariate surveillance; 3.8 Concluding remarks; Acknowledgment; Part II Basic Methods for Spatial and Syndromic Surveillance; 4 Spatial and spatio-temporal disease analysis; 4.1 Introduction; 4.2 Disease mapping and map reconstruction; 4.3 Disease map restoration; 4.3.1 Simple statistical representations; 4.3.2 Basic models
4.3.3 A simple overdispersion model4.3.4 Advanced Bayesian models; 4.4 Residuals and goodness of fit; 4.5 Spatio-temporal analysis; 4.6 Surveillance issues; 5 Generalized linear models and generalized linear mixed models for small-area surveillance; 5.1 Introduction; 5.2 Surveillance using small-area modeling; 5.2.1 Example; 5.2.2 Using the model results; 5.3 Alternate model formulations; 5.3.1 Fixed effects logistic regression; 5.3.2 Poisson regression models; 5.4 Practical variations; 5.5 Data; 5.5.1 Developing and defining syndromes; 5.6 Evaluation
5.6.1 Fixed and random effects monthly models
Record Nr. UNINA-9910143707503321
Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Spatial and syndromic surveillance for public health [[electronic resource] /] / edited by Andrew B. Lawson, Ken Kleinman
Spatial and syndromic surveillance for public health [[electronic resource] /] / edited by Andrew B. Lawson, Ken Kleinman
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Descrizione fisica 1 online resource (285 p.)
Disciplina 614.4
Altri autori (Persone) LawsonAndrew (Andrew B.)
KleinmanKen
Soggetto topico Public health surveillance
Epidemiology
ISBN 1-280-23853-4
9786610238538
0-470-09250-5
0-470-09249-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Spatial and Syndromic Surveillance for Public Health; Contents; Preface; List of Contributors; 1 Introduction: Spatial and syndromic surveillance for public health; 1.1 What is public health surveillance?; 1.1.1 Spatial surveillance; 1.1.2 Syndromic surveillance; 1.2 The increased importance of public health surveillance; 1.3 Geographic information, cluster detection and spatial surveillance; 1.4 Surveillance and screening; 1.5 Overview of process control and mapping; 1.5.1 Process control methodology; 1.5.2 The analysis of maps and surveillance; 1.6 The purpose of this book
1.6.1 Statistical surveillance and methodological development in a public health context1.6.2 The statistician's role in surveillance; 1.7 The contents of this book; Part I Introduction to Temporal Surveillance; 2 Overview of temporal surveillance; 2.1 Introduction; 2.1.1 Surveillance systems; 2.1.2 Surveillance attributes; 2.1.3 Early detection of unusual health events; 2.2 Statistical methods; 2.2.1 Historical limits method; 2.2.2 Process control charts; 2.2.3 Time-series analysis; 2.3 Conclusion; 3 Optimal surveillance; 3.1 Introduction
3.2 Optimality for a fixed sample and for on-line surveillance3.3 Specification of the statistical surveillance problem; 3.4 Evaluations of systems for surveillance; 3.4.1 Measures for a fixed sample situation adopted for surveillance; 3.4.2 False alarms; 3.4.3 Delay of the alarm; 3.4.4 Predictive value; 3.5 Optimality criteria; 3.5.1 Minimal expected delay; 3.5.2 Minimax optimality; 3.5.3 Average run length; 3.6 Optimality of some standard methods; 3.6.1 The likelihood ratio method; 3.6.2 The Shewhart method; 3.6.3 The CUSUM method; 3.6.4 Moving average and window-based methods
3.6.5 Exponentially weighted moving average methods3.7 Special aspects of optimality for surveillance of public health; 3.7.1 Gradual changes during outbreaks of diseases; 3.7.2 Change between unknown incidences; 3.7.3 Spatial and other multivariate surveillance; 3.8 Concluding remarks; Acknowledgment; Part II Basic Methods for Spatial and Syndromic Surveillance; 4 Spatial and spatio-temporal disease analysis; 4.1 Introduction; 4.2 Disease mapping and map reconstruction; 4.3 Disease map restoration; 4.3.1 Simple statistical representations; 4.3.2 Basic models
4.3.3 A simple overdispersion model4.3.4 Advanced Bayesian models; 4.4 Residuals and goodness of fit; 4.5 Spatio-temporal analysis; 4.6 Surveillance issues; 5 Generalized linear models and generalized linear mixed models for small-area surveillance; 5.1 Introduction; 5.2 Surveillance using small-area modeling; 5.2.1 Example; 5.2.2 Using the model results; 5.3 Alternate model formulations; 5.3.1 Fixed effects logistic regression; 5.3.2 Poisson regression models; 5.4 Practical variations; 5.5 Data; 5.5.1 Developing and defining syndromes; 5.6 Evaluation
5.6.1 Fixed and random effects monthly models
Record Nr. UNINA-9910830854103321
Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Spatial and syndromic surveillance for public health / / edited by Andrew B. Lawson, Ken Kleinman
Spatial and syndromic surveillance for public health / / edited by Andrew B. Lawson, Ken Kleinman
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Descrizione fisica 1 online resource (285 p.)
Disciplina 614.4
Altri autori (Persone) LawsonAndrew (Andrew B.)
KleinmanKen
Soggetto topico Public health surveillance
Epidemiology
ISBN 9786610238538
9781280238536
1280238534
9780470092507
0470092505
9780470092491
0470092491
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Spatial and Syndromic Surveillance for Public Health; Contents; Preface; List of Contributors; 1 Introduction: Spatial and syndromic surveillance for public health; 1.1 What is public health surveillance?; 1.1.1 Spatial surveillance; 1.1.2 Syndromic surveillance; 1.2 The increased importance of public health surveillance; 1.3 Geographic information, cluster detection and spatial surveillance; 1.4 Surveillance and screening; 1.5 Overview of process control and mapping; 1.5.1 Process control methodology; 1.5.2 The analysis of maps and surveillance; 1.6 The purpose of this book
1.6.1 Statistical surveillance and methodological development in a public health context1.6.2 The statistician's role in surveillance; 1.7 The contents of this book; Part I Introduction to Temporal Surveillance; 2 Overview of temporal surveillance; 2.1 Introduction; 2.1.1 Surveillance systems; 2.1.2 Surveillance attributes; 2.1.3 Early detection of unusual health events; 2.2 Statistical methods; 2.2.1 Historical limits method; 2.2.2 Process control charts; 2.2.3 Time-series analysis; 2.3 Conclusion; 3 Optimal surveillance; 3.1 Introduction
3.2 Optimality for a fixed sample and for on-line surveillance3.3 Specification of the statistical surveillance problem; 3.4 Evaluations of systems for surveillance; 3.4.1 Measures for a fixed sample situation adopted for surveillance; 3.4.2 False alarms; 3.4.3 Delay of the alarm; 3.4.4 Predictive value; 3.5 Optimality criteria; 3.5.1 Minimal expected delay; 3.5.2 Minimax optimality; 3.5.3 Average run length; 3.6 Optimality of some standard methods; 3.6.1 The likelihood ratio method; 3.6.2 The Shewhart method; 3.6.3 The CUSUM method; 3.6.4 Moving average and window-based methods
3.6.5 Exponentially weighted moving average methods3.7 Special aspects of optimality for surveillance of public health; 3.7.1 Gradual changes during outbreaks of diseases; 3.7.2 Change between unknown incidences; 3.7.3 Spatial and other multivariate surveillance; 3.8 Concluding remarks; Acknowledgment; Part II Basic Methods for Spatial and Syndromic Surveillance; 4 Spatial and spatio-temporal disease analysis; 4.1 Introduction; 4.2 Disease mapping and map reconstruction; 4.3 Disease map restoration; 4.3.1 Simple statistical representations; 4.3.2 Basic models
4.3.3 A simple overdispersion model4.3.4 Advanced Bayesian models; 4.4 Residuals and goodness of fit; 4.5 Spatio-temporal analysis; 4.6 Surveillance issues; 5 Generalized linear models and generalized linear mixed models for small-area surveillance; 5.1 Introduction; 5.2 Surveillance using small-area modeling; 5.2.1 Example; 5.2.2 Using the model results; 5.3 Alternate model formulations; 5.3.1 Fixed effects logistic regression; 5.3.2 Poisson regression models; 5.4 Practical variations; 5.5 Data; 5.5.1 Developing and defining syndromes; 5.6 Evaluation
5.6.1 Fixed and random effects monthly models
Record Nr. UNINA-9911020015403321
Chichester, West Sussex, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui