Biomedical Statistics and Informatics

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Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia

Received: 16 December 2016    Accepted: 27 December 2016    Published: 13 February 2017
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Abstract

The purpose of this study is to investigate adult mortality variations among regional states in Ethiopia. Data from Ethiopian Demographic and Health Survey (EDHS 2011) are used. Multilevel logistic regression model is fitted to the data. The findings show that the correlates of adult mortality are adult's age, age of household head, sex of household head, wealth index, type of toilet facility, and type of cooking fuels. The between-region variance is estimated to be 0.1727 which is significant at 5% level of significance, indicating that variation of adult mortality among regional states is non-zero. The intra-correlation is estimated to be 0.0099, suggesting that about 1% of the variation in adult mortality could be attributed to differences across regional states. The variance of the random coefficient model is statistically significant, implying the presence of adult mortality variation among regional states of the country. The deviance statistic is about 4113.945 and it is compared with Chi-square at difference of full and empty model with degree of freedom 33.924 at df 22 and p-value < 0.000. This reveals that there is enough evidence against null hypothesis. Therefore, the multilevel model consisting the explanatory variables is considered the final model. It revealed that the random coefficient multilevel logistic regression analysis suggests that there exist considerable differences in adult mortality across regions in the country.

DOI 10.11648/j.bsi.20170201.16
Published in Biomedical Statistics and Informatics (Volume 2, Issue 1, March 2017)
Page(s) 27-36
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), 2024. Published by Science Publishing Group

Keywords

Adult Mortality, EDHS, Ethiopia, Heterogeneity, Logistic Regression Model, Multilevel Model, Random Effects, Regional Variation

References
[1] World Health Organization WHO (2014). World Health Statistics 2014. Geneva.
[2] Richard G., Hummer, A. and Patrick, A. (2003). Adult Mortality. Working Paper POP 2003, 0003.
[3] Chasimpha, S., McLean, E, Chihana, M, Kachiwanda, L, Koole1, O, Tafatatha, T, Mvula, H, Nyirenda, M, Crampin, AC, Glynn, JR (2015). Patterns and Risk Factors for Deaths from External Causes in Rural Malawi over 10 Years: A Prospective Population-based Study. BMC Public Health, 15:1036. DOI: 10.1186/s12889-015-2323-z.
[4] CSA (2011). Ethiopia Demographic and Health Survey Report.
[5] Hosmer D and Lemeshow S (2000). Applied Logistic Regression. Second Edition. New York: John Wiley and Sons.
[6] Agresti, A. (1996), Categorical Data Analysis. Second edition. University of Florida, John Wiley & sons, INC.,Publication
[7] Bewick L. and Jonathan B. (2005). Statistics Review 14: Logistic Regression.
[8] Long, J. S. (1997). Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage.
[9] Connel A. A. (2006). Logistic Regression Models for Ordinal Response Variables. Thousand Oaks: Sage. QASS No. 146.
[10] Taper M. L. (2004). Model Identification from Many Candidates. The Nature of Scientific Evidence. M. L. Taper and S. R. Lele, Editors. The University of Chicago Press, Chicago, IL, USA. P 3-16.
[11] Saikia, N and Bhat, P. N. (2008), Factors Affecting Adult Mortality in India: An Analysis of National Family Health Surveys of 1992-1993 and 1998-99. Journal of Demography India, Vol. 37.
[12] Zimmer, Z., Kaneda, T, Spress, L (2006). Urban Versus Rural Mortality among Older Adults in China. Working paper, New York, New York 10017 USA.
Author Information
  • Department of Statistics, Arba Minch University, Arba Minch, Ethiopia

  • Schools of Mathematical and Statistical Sciences, Hawassa University, Hawassa, Ethiopia

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    Kassaye Wudu Seid, Ayele Taye Goshu. (2017). Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia. Biomedical Statistics and Informatics, 2(1), 27-36. https://doi.org/10.11648/j.bsi.20170201.16

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    Kassaye Wudu Seid; Ayele Taye Goshu. Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia. Biomed. Stat. Inform. 2017, 2(1), 27-36. doi: 10.11648/j.bsi.20170201.16

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    AMA Style

    Kassaye Wudu Seid, Ayele Taye Goshu. Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia. Biomed Stat Inform. 2017;2(1):27-36. doi: 10.11648/j.bsi.20170201.16

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  • @article{10.11648/j.bsi.20170201.16,
      author = {Kassaye Wudu Seid and Ayele Taye Goshu},
      title = {Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia},
      journal = {Biomedical Statistics and Informatics},
      volume = {2},
      number = {1},
      pages = {27-36},
      doi = {10.11648/j.bsi.20170201.16},
      url = {https://doi.org/10.11648/j.bsi.20170201.16},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.bsi.20170201.16},
      abstract = {The purpose of this study is to investigate adult mortality variations among regional states in Ethiopia. Data from Ethiopian Demographic and Health Survey (EDHS 2011) are used. Multilevel logistic regression model is fitted to the data. The findings show that the correlates of adult mortality are adult's age, age of household head, sex of household head, wealth index, type of toilet facility, and type of cooking fuels. The between-region variance is estimated to be 0.1727 which is significant at 5% level of significance, indicating that variation of adult mortality among regional states is non-zero. The intra-correlation is estimated to be 0.0099, suggesting that about 1% of the variation in adult mortality could be attributed to differences across regional states. The variance of the random coefficient model is statistically significant, implying the presence of adult mortality variation among regional states of the country. The deviance statistic is about 4113.945 and it is compared with Chi-square at difference of full and empty model with degree of freedom 33.924 at df 22 and p-value < 0.000. This reveals that there is enough evidence against null hypothesis. Therefore, the multilevel model consisting the explanatory variables is considered the final model. It revealed that the random coefficient multilevel logistic regression analysis suggests that there exist considerable differences in adult mortality across regions in the country.},
     year = {2017}
    }
    

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    AB  - The purpose of this study is to investigate adult mortality variations among regional states in Ethiopia. Data from Ethiopian Demographic and Health Survey (EDHS 2011) are used. Multilevel logistic regression model is fitted to the data. The findings show that the correlates of adult mortality are adult's age, age of household head, sex of household head, wealth index, type of toilet facility, and type of cooking fuels. The between-region variance is estimated to be 0.1727 which is significant at 5% level of significance, indicating that variation of adult mortality among regional states is non-zero. The intra-correlation is estimated to be 0.0099, suggesting that about 1% of the variation in adult mortality could be attributed to differences across regional states. The variance of the random coefficient model is statistically significant, implying the presence of adult mortality variation among regional states of the country. The deviance statistic is about 4113.945 and it is compared with Chi-square at difference of full and empty model with degree of freedom 33.924 at df 22 and p-value < 0.000. This reveals that there is enough evidence against null hypothesis. Therefore, the multilevel model consisting the explanatory variables is considered the final model. It revealed that the random coefficient multilevel logistic regression analysis suggests that there exist considerable differences in adult mortality across regions in the country.
    VL  - 2
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