Summary of the number of events in the grid cells for all the non-zero cell counts at various spatial scales for the Humberside dataset
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The dataset was gathered to investigate the impact of changes in spatial scale on model outcome for a set of spatial structures and to evaluate the performance of various Bayesian spatial smoothness priors for
spatial dependence, namely an intrinsic Gaussian Markov random field
(IGMRF), a second-order random walk (RW2D) on a lattice, and a Gaussian
field with Matérn correlation function.The current dataset draws upon the Humberside case study to complete the investigation.
The Humberside case study portrays natural phenomena to investigate the impact of spatial scales and spatial smoothing on modelling outcomes to complement a simulation study. The data contained 62 cases of childhood leukaemia and lymphoma diagnosed in the North Humberside region of England between 1974 and 1986, and 141 controls selected at random from the birth register for the same period. Spatial location of each individual's home address (actually, the centroid for the postal code) was given in the dataset. The dataset had a polygonal observation window; for the analysis, we created a 72.1 km×60.8 km rectangular window to enclose all events.
The Humberside case study portrays natural phenomena to investigate the impact of spatial scales and spatial smoothing on modelling outcomes to complement a simulation study. The data contained 62 cases of childhood leukaemia and lymphoma diagnosed in the North Humberside region of England between 1974 and 1986, and 141 controls selected at random from the birth register for the same period. Spatial location of each individual's home address (actually, the centroid for the postal code) was given in the dataset. The dataset had a polygonal observation window; for the analysis, we created a 72.1 km×60.8 km rectangular window to enclose all events.
The dataset presents a summary of the
number of events in the grid cells for all the non-zero cell counts at
various spatial scales for the Humberside case study.
Geographical area of data collection
kmlPolyCoords
153.025013,-27.476409
Publications
Kang, Su Yun, McGree, James, & Mengersen, Kerrie (2013) The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model. PLoS ONE, 18(10).
http://dx.doi.org/10.1371/journal.pone.0075957
Research areas
Humberside
Non-zero
Grid
Counts
Spatial
Scales
Cells
Cite this collection
Mengersen,Kerrie; Kang,Su Yun; McGree,James. (2016): Summary of the number of events in the grid cells for all the non-zero cell counts at various spatial scales for the Humberside dataset. [Queensland University of Technology]. https://doi.org/10.4225/09/5885a243b32cb
Related information
The work has been supported by the Cooperative Research Centre for Spatial Information
http://dx.doi.org/http://www.crcsi.com.au/
Access the data
Data file types
csv
Licence
Copyright
© 2013 Kang et al.
Dates of data collection
From 2013-01-01 to 2013-09-30
Connections
Has chief investigator
Contacts
Name: Su Yun Kang
Email: s7.kang@qut.edu.au
Other
Date record created:
2014-07-01T10:31:21
Date record modified:
2020-11-06T15:21:31
Record status:
Published - Open Access