Coverart for item
The Resource Spatial analysis in epidemiology, Dirk U. Pfeiffer [and others]

Spatial analysis in epidemiology, Dirk U. Pfeiffer [and others]

Label
Spatial analysis in epidemiology
Title
Spatial analysis in epidemiology
Statement of responsibility
Dirk U. Pfeiffer [and others]
Contributor
Subject
Genre
Language
eng
Summary
Providing a practical, comprehensive and up-to-date overview of the use of spatial statistics in epidemiology, this book examines spatial analytical methods in conjunction with GIS and remotely sensed data to provide insights into the patterns and processes that underlie disease transmission
Member of
Cataloging source
N$T
Dewey number
614.40727
Illustrations
  • illustrations
  • maps
Index
index present
LC call number
RA652.2.M3
LC item number
S63 2008eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
NLM call number
WA 950
NLM item number
S7377 2008
http://library.link/vocab/relatedWorkOrContributorDate
1958-
http://library.link/vocab/relatedWorkOrContributorName
Pfeiffer, Dirk
Series statement
Oxford biology
http://library.link/vocab/subjectName
  • Epidemiology
  • Medical geography
  • Epidemiologic Methods
  • Geography
  • MEDICAL
  • MEDICAL
  • Epidemiology
Label
Spatial analysis in epidemiology, Dirk U. Pfeiffer [and others]
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Abbreviations; Preface; 1 Introduction; 1.1 Framework for spatial analysis; 1.2 Scientific literature and conferences; 1.3 Software; 1.4 Spatial data; 1.5 Book content and structure; 1.5.1 Datasets used; 2 Spatial data; 2.1 Introduction; 2.2 Spatial data and GIS; 2.2.1 Data types; 2.2.2 Data storage and interchange; 2.2.3 Data collection and management; 2.2.4 Data quality; 2.3 Spatial effects; 2.3.1 Spatial heterogeneity and dependence; 2.3.2 Edge effects; 2.3.3 Representing neighbourhood relationships; 2.3.4 Statistical significance testing with spatial data; 2.4 Conclusion
  • 3 Spatial visualization3.1 Introduction; 3.2 Point data; 3.3 Aggregated data; 3.4 Continuous data; 3.5 Effective data display; 3.5.1 Media, scale, and area; 3.5.2 Dynamic display; 3.5.3 Cartography; 3.6 Conclusion; 4 Spatial clustering of disease and global estimates of spatial clustering; 4.1 Introduction; 4.2 Disease cluster alarms and cluster investigation; 4.3 Statistical concepts relevant to cluster analysis; 4.3.1 Stationarity, isotropy, and first- and second-order effects; 4.3.2 Monte Carlo simulation; 4.3.3 Statistical power of clustering methods; 4.4 Methods for aggregated data
  • 4.4.1 Moran's I4.4.2 Geary's c; 4.4.3 Tango's excess events test (EET) and maximized excess events test (MEET); 4.5 Methods for point data; 4.5.1 Cuzick and Edwards' k-nearest neighbour test; 4.5.2 Ripley's K-function; 4.5.3 Rogerson's cumulative sum (CUSUM) method; 4.6 Investigating space-time clustering; 4.6.1 The Knox test; 4.6.2 The space-time k-function; 4.6.3 The Ederer-Myers-Mantel (EMM) test; 4.6.4 Mantel's test; 4.6.5 Barton's test; 4.6.6 Jacquez's k nearest neighbours test; 4.7 Conclusion; 5 Local estimates of spatial clustering; 5.1 Introduction; 5.2 Methods for aggregated data
  • 5.2.1 Getis and Ord's local Gi(d) statistic5.2.2 Local Moran test; 5.3 Methods for point data; 5.3.1 Openshaw's Geographical Analysis Machine (GAM); 5.3.2 Turnbull's Cluster Evaluation Permutation Procedure (CEPP); 5.3.3 Besag and Newell's method; 5.3.4 Kulldorff's spatial scan statistic; 5.3.5 Non-parametric spatial scan statistics; 5.3.6 Example of local cluster detection; 5.4 Detecting clusters around a source (focused tests); 5.4.1 Stone's test; 5.4.2 The Lawson-Waller score test; 5.4.3 Bithell's linear risk score tests; 5.4.4 Diggle's test
  • 5.4.5 Kulldorff's focused spatial scan statistic5.5 Space-time cluster detection; 5.5.1 Kulldorff's space-time scan statistic; 5.5.2 Example of space-time cluster detection; 5.6 Conclusion; 6 Spatial variation in risk; 6.1 Introduction; 6.2 Smoothing based on kernel functions; 6.3 Smoothing based on Bayesian models; 6.4 Spatial interpolation; 6.5 Conclusion; 7 Identifying factors associated with the spatial distribution of disease; 7.1 Introduction; 7.2 Principles of regression modelling; 7.2.1 Linear regression; 7.2.2 Poisson regression; 7.2.3 Logistic regression; 7.2.4 Multilevel models
Control code
236792155
Dimensions
unknown
Extent
1 online resource (xii, 142 pages)
File format
unknown
Form of item
online
Isbn
9780191523274
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color), maps
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)236792155
Label
Spatial analysis in epidemiology, Dirk U. Pfeiffer [and others]
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Abbreviations; Preface; 1 Introduction; 1.1 Framework for spatial analysis; 1.2 Scientific literature and conferences; 1.3 Software; 1.4 Spatial data; 1.5 Book content and structure; 1.5.1 Datasets used; 2 Spatial data; 2.1 Introduction; 2.2 Spatial data and GIS; 2.2.1 Data types; 2.2.2 Data storage and interchange; 2.2.3 Data collection and management; 2.2.4 Data quality; 2.3 Spatial effects; 2.3.1 Spatial heterogeneity and dependence; 2.3.2 Edge effects; 2.3.3 Representing neighbourhood relationships; 2.3.4 Statistical significance testing with spatial data; 2.4 Conclusion
  • 3 Spatial visualization3.1 Introduction; 3.2 Point data; 3.3 Aggregated data; 3.4 Continuous data; 3.5 Effective data display; 3.5.1 Media, scale, and area; 3.5.2 Dynamic display; 3.5.3 Cartography; 3.6 Conclusion; 4 Spatial clustering of disease and global estimates of spatial clustering; 4.1 Introduction; 4.2 Disease cluster alarms and cluster investigation; 4.3 Statistical concepts relevant to cluster analysis; 4.3.1 Stationarity, isotropy, and first- and second-order effects; 4.3.2 Monte Carlo simulation; 4.3.3 Statistical power of clustering methods; 4.4 Methods for aggregated data
  • 4.4.1 Moran's I4.4.2 Geary's c; 4.4.3 Tango's excess events test (EET) and maximized excess events test (MEET); 4.5 Methods for point data; 4.5.1 Cuzick and Edwards' k-nearest neighbour test; 4.5.2 Ripley's K-function; 4.5.3 Rogerson's cumulative sum (CUSUM) method; 4.6 Investigating space-time clustering; 4.6.1 The Knox test; 4.6.2 The space-time k-function; 4.6.3 The Ederer-Myers-Mantel (EMM) test; 4.6.4 Mantel's test; 4.6.5 Barton's test; 4.6.6 Jacquez's k nearest neighbours test; 4.7 Conclusion; 5 Local estimates of spatial clustering; 5.1 Introduction; 5.2 Methods for aggregated data
  • 5.2.1 Getis and Ord's local Gi(d) statistic5.2.2 Local Moran test; 5.3 Methods for point data; 5.3.1 Openshaw's Geographical Analysis Machine (GAM); 5.3.2 Turnbull's Cluster Evaluation Permutation Procedure (CEPP); 5.3.3 Besag and Newell's method; 5.3.4 Kulldorff's spatial scan statistic; 5.3.5 Non-parametric spatial scan statistics; 5.3.6 Example of local cluster detection; 5.4 Detecting clusters around a source (focused tests); 5.4.1 Stone's test; 5.4.2 The Lawson-Waller score test; 5.4.3 Bithell's linear risk score tests; 5.4.4 Diggle's test
  • 5.4.5 Kulldorff's focused spatial scan statistic5.5 Space-time cluster detection; 5.5.1 Kulldorff's space-time scan statistic; 5.5.2 Example of space-time cluster detection; 5.6 Conclusion; 6 Spatial variation in risk; 6.1 Introduction; 6.2 Smoothing based on kernel functions; 6.3 Smoothing based on Bayesian models; 6.4 Spatial interpolation; 6.5 Conclusion; 7 Identifying factors associated with the spatial distribution of disease; 7.1 Introduction; 7.2 Principles of regression modelling; 7.2.1 Linear regression; 7.2.2 Poisson regression; 7.2.3 Logistic regression; 7.2.4 Multilevel models
Control code
236792155
Dimensions
unknown
Extent
1 online resource (xii, 142 pages)
File format
unknown
Form of item
online
Isbn
9780191523274
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color), maps
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)236792155

Library Locations

    • UMKCBorrow it
      800 E 51st St, Kansas City, MO, 64110, US
      39.035061 -94.576518
    • Health Sciences LibraryBorrow it
      2411 Holmes St, Kansas City, Kansas City, MO, 64108, US
      39.083418 -94.575323
    • Leon E. Bloch Law LibraryBorrow it
      500 E. 52nd Street, Kansas City, MO, 64110, US
      39.032488 -94.581967
Processing Feedback ...