dc.contributor.author |
Mutwiri, Robert M. |
|
dc.date.accessioned |
2021-10-07T11:50:47Z |
|
dc.date.available |
2021-10-07T11:50:47Z |
|
dc.date.issued |
2016-03 |
|
dc.identifier.citation |
Journal Of Humanities And Social Science (IOSR-JHSS) Volume 21, Issue 3, Ver. II, PP 70-77 |
en_US |
dc.identifier.issn |
2279-0837 |
|
dc.identifier.issn |
2279-0845 |
|
dc.identifier.uri |
https://www.iosrjournals.org/iosr-jhss/papers/Vol.%2021%20Issue3/Version-2/K2103027077.pdf |
|
dc.identifier.uri |
http://repository.seku.ac.ke/handle/123456789/6353 |
|
dc.description |
DOI: 10.9790/0837-2103027077 |
en_US |
dc.description.abstract |
This paper addresses the problem of monitoring the infant and child mortality from point referenced
data. Indicators of the determinants of child survival based on Mosley and Chen framework are derived and
used to model the spatial distribution of infant mortality. Spatial generalised linear model which assumes a
Bernoulli dis-tribution to model the indicator determinants of child survival. A smooth map of the predicted
values at both sampled and the un sampled is produced. We find evidence of spatial autocorrelation in the data
and the smooth map indicates the hot spot of infant mortality where more resources are needed to attain the
millennium develop-ment goal four |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Infant mortality |
en_US |
dc.subject |
Indicators |
en_US |
dc.subject |
Geostatistics |
en_US |
dc.subject |
Spatial Generalized Linear models |
en_US |
dc.subject |
Bayesian Spatial Modelling |
en_US |
dc.subject |
Mapping |
en_US |
dc.title |
Spatial modelling and mapping of socio-demographic determinants of infant mortality in Kenya |
en_US |
dc.type |
Article |
en_US |