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Geostatistics Analysis of Infant Mortality Rate in Ethiopia

Received: 17 May 2017     Accepted: 24 May 2017     Published: 10 July 2017
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Abstract

In this paper, spatial statistical analysis of infant mortality rate in Ethiopia is addressed. The analysis investigated of a significance spatial autocorrelation attendance as well as an adapting of a generalized linear mixed model with spatial covariance structure. The results showed the distribution is much spatially associated. Some geographical, economical and healthy variables are used to estimate the model. Several examined variables have a significant effect in the model contrast to other have an insignificant impact. The results highlight the role of improving education to decline the risk of infant mortality rate. Male and children with extra weight are higher exposed and the risk is highly different from one zone to another.

Published in American Journal of Theoretical and Applied Statistics (Volume 6, Issue 4)
DOI 10.11648/j.ajtas.20170604.17
Page(s) 209-213
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Spatial Statistics, Infant Mortality, Generalized Models, Mixed Models, Moran’s I

References
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[2] WHO (2016), Under-five mortality, Available at http://www.who.int/gho/child_health/mortality/mortality_under_five_text/en/index.html. 15 January 2017.
[3] Center for Disease Control and Prevention (2016). “Infant Mortality,” http://www.cdc.gov/reproductivehealth/maternalinfanthealth/infantmortality.htm.
[4] Daniel Reidpath and Pascale Allotey (2003). “Infant Mortality Rate as an Indicator of Population Health”, Journal of Epidemiology and Community Health, 57, 344–346.
[5] United Nations (2005), Human Development Report, New York, UNDP, 4.
[6] WHO (2011). “Newborn death and illness”, http://www.who.int/pmnch/media/press_materials/fs/fs_newborndealth_illness/en.
[7] World Bank (2016). “Mortality rate, Infant”, http://data.worldbank.org/indicator/SP.DYN.IMRT.IN.
[8] Holmberg, H and HäggströmLundevaller E. (2015), “A test for robust detection of residual spatial autocorrelation with application to mortality rates in Sweden”, Spatial Statistics, 14, 365-381.
[9] Dawit G. Ayele&Temesgen T. Zewotir (2016), “Childhood mortality spatial distribution in Ethiopia”, Journal of Applied Statistics, 43(15), 2813-2828.
[10] LICHSTEIN, JEREMY W., SIMONS, THEODORE R., SHRINER, SUSAN A., AND FRANZREB, KATHLEEN E. (2002). “SPATIALAUTOCORRELATION AND AUTOREGRESSIVE MODELS IN ECOLOGY”, Ecological Monographs, 72 (3), 445–463.
[11] Getis, Arthur (2008), “A History of the Concept of Spatial Autocorrelation: A Geographer’s Perspective”, Geographical Analysis, 40, 297–309.
[12] Chou, Y. (1997), “Exploring Spatial Analysis in Geographic Information Systems”, Onward Press, Santa Fe.
[13] Anselin, L. (1992), “SpaceStat Tutorial: A Workbook for Using SpaceStat in the analysis of Spatial Data”, Typescript. University of Illinois at Urbana-Champaign, pp. 8-67.
[14] Anselin, L. (1995), “Local indicators of spatial association -LISA. Geographical Analysis”, 27, 93-105.
[15] Moran, P. A. P. (1950), Notes on Continuous Stochastic Phenomena, Biometrika 37 (1): 17–23.
[16] Geary, R. C. (1954), The Contiguity Ratio and Statistical Mapping, The Incorporated Statistician, 5 (3): 115–145.
[17] Getis, A and Ord, J. K. (1992), The analysis of spatial association by use of distance statistics, Geographic Analtsis, 24 (3): 189-206.
[18] Melecky, Lukas (2015), “Spatial Autocorrelation Method for Local Analysis of The EU”, Procedia Economics and Finance, 23, 1102 – 1109.
[19] Osman, Montasir A. (2016). “GIS Use to Analyze Distribution of Malaria Spread in Kassala State”, 5th International Conference of Union of Arab Statisticians, Cairo. Feb 9-10.
[20] Dale, Mark (2002). “Spatial Autocorrelation and Statistical Tests in Ecology”, Ecoscience, 9 (2), 162-167.
[21] McCullagh, P, &Nelder, J. A. (1989). Generalized Linear Models, 2nd ed. Chapman & Hall/CRC Press.
[22] Breslow, N. E. & Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association, 88 (421), pp 9-25.
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[25] Fitzmaurice, G. M.; Laird, N. M.; Ware, J.. (2011), Applied Longitudinal Analysis (2nd ed.), John Wiley & Sons.
[26] CSA, Central Statistics Agency of Ethiopia and ORC Macro (2012): Ethiopia demographic and Health Survey 2011, Central Statistics Agency and ORC Macro, Addis Ababa and Calverton, MD.
Cite This Article
  • APA Style

    Montasir Ahmed Osman Mohamed. (2017). Geostatistics Analysis of Infant Mortality Rate in Ethiopia. American Journal of Theoretical and Applied Statistics, 6(4), 209-213. https://doi.org/10.11648/j.ajtas.20170604.17

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    ACS Style

    Montasir Ahmed Osman Mohamed. Geostatistics Analysis of Infant Mortality Rate in Ethiopia. Am. J. Theor. Appl. Stat. 2017, 6(4), 209-213. doi: 10.11648/j.ajtas.20170604.17

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    AMA Style

    Montasir Ahmed Osman Mohamed. Geostatistics Analysis of Infant Mortality Rate in Ethiopia. Am J Theor Appl Stat. 2017;6(4):209-213. doi: 10.11648/j.ajtas.20170604.17

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  • @article{10.11648/j.ajtas.20170604.17,
      author = {Montasir Ahmed Osman Mohamed},
      title = {Geostatistics Analysis of Infant Mortality Rate in Ethiopia},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {6},
      number = {4},
      pages = {209-213},
      doi = {10.11648/j.ajtas.20170604.17},
      url = {https://doi.org/10.11648/j.ajtas.20170604.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20170604.17},
      abstract = {In this paper, spatial statistical analysis of infant mortality rate in Ethiopia is addressed. The analysis investigated of a significance spatial autocorrelation attendance as well as an adapting of a generalized linear mixed model with spatial covariance structure. The results showed the distribution is much spatially associated. Some geographical, economical and healthy variables are used to estimate the model. Several examined variables have a significant effect in the model contrast to other have an insignificant impact. The results highlight the role of improving education to decline the risk of infant mortality rate. Male and children with extra weight are higher exposed and the risk is highly different from one zone to another.},
     year = {2017}
    }
    

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    AU  - Montasir Ahmed Osman Mohamed
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    PY  - 2017
    N1  - https://doi.org/10.11648/j.ajtas.20170604.17
    DO  - 10.11648/j.ajtas.20170604.17
    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
    SP  - 209
    EP  - 213
    PB  - Science Publishing Group
    SN  - 2326-9006
    UR  - https://doi.org/10.11648/j.ajtas.20170604.17
    AB  - In this paper, spatial statistical analysis of infant mortality rate in Ethiopia is addressed. The analysis investigated of a significance spatial autocorrelation attendance as well as an adapting of a generalized linear mixed model with spatial covariance structure. The results showed the distribution is much spatially associated. Some geographical, economical and healthy variables are used to estimate the model. Several examined variables have a significant effect in the model contrast to other have an insignificant impact. The results highlight the role of improving education to decline the risk of infant mortality rate. Male and children with extra weight are higher exposed and the risk is highly different from one zone to another.
    VL  - 6
    IS  - 4
    ER  - 

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Author Information
  • Scientific Research and Development Center, Nawroz University, Kurdistan Region, Iraq

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