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.
| Published in | Biomedical Statistics and Informatics (Volume 2, Issue 1) |
| DOI | 10.11648/j.bsi.20170201.16 |
| 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), 2017. Published by Science Publishing Group |
Adult Mortality, EDHS, Ethiopia, Heterogeneity, Logistic Regression Model, Multilevel Model, Random Effects, Regional Variation
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APA Style
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
ACS 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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Download@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://article.sciencepublishinggroup.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}
}
TY - JOUR T1 - Multilevel Logistic Modeling of Adult Mortality Among Regional States in Ethiopia AU - Kassaye Wudu Seid AU - Ayele Taye Goshu Y1 - 2017/02/13 PY - 2017 N1 - https://doi.org/10.11648/j.bsi.20170201.16 DO - 10.11648/j.bsi.20170201.16 T2 - Biomedical Statistics and Informatics JF - Biomedical Statistics and Informatics JO - Biomedical Statistics and Informatics SP - 27 EP - 36 PB - Science Publishing Group SN - 2578-8728 UR - https://doi.org/10.11648/j.bsi.20170201.16 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 IS - 1 ER -
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