Midlands State University Library

Modelling spatial heterogeneity and anisotropy: child anaemia, sanitation and basic infrastructure in sub-Saharan Africa (Record no. 160736)

MARC details
000 -LEADER
fixed length control field 02353nam a22002417a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221208140128.0
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fixed length control field 221208b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Mainardi , Stefano
Relator term author
245 10 - TITLE STATEMENT
Title Modelling spatial heterogeneity and anisotropy: child anaemia, sanitation and basic infrastructure in sub-Saharan Africa
Statement of responsibility, etc. created by Stefano Mainardi
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Warsaw:
Name of producer, publisher, distributor, manufacturer Taylor & francis,
Date of production, publication, distribution, manufacture, or copyright notice 2012.
336 ## - CONTENT TYPE
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Content type term text
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337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
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440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
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520 ## - SUMMARY, ETC.
Summary, etc. Public interventions in support of public health and housing in developing countries could benefit from better understanding of spatial heterogeneity and anisotropy. Estimation of directional variation within geographically weighted regression (GWR) faces problems of local parameter instability, border effects and, if extended to non- spatial attributes, potential endogeneity. This study formulates a GWR model where anisotropy is filtered out based on information from directional variograms. Along with classical regressions, the approach is applied to investigate child anaemia and its associations with household characteristics, sanitation and basic infrastructure in 173 regions of sub-Saharan Africa. Based on ordinary least squares (OLS) results, anaemia prevalence rates are up to three times more responsive to child morbidity (related to malaria and other diseases) than to other covariates. GWR estimates provide similar indications, but also point to poor sanitation facilities as a cofactor of severe anaemia particularly in east and southern Africa. The anisotropy-adjusted GWR is spatially stationary in residuals, and itsestimated local parameters are less collinear than GWR with no adjustment. However, similar explanatory power and lack of significant bias in parameters estimated by the latter suggest that directional variation is largely captured by modelled co-movements among the variables.<br/><br/>Keywords:<br/><br/> housing standards and infrastructure<br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/> <br/><br/> <br/><br/> <br/> <br/><br/><br/>
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element geographically weighted regression
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element variogram
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element public health
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1080/13658816.2011.585612
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Date last seen Copy number Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 14/01/2014   G70.2 INT 08/12/2022 SP17880 08/12/2022 Journal Article For in-house use only