A A Statistical Analysis of the Number of Infant Mortality in Peninsular Malaysia

  • Yati Ashikin Abd Wahab
  • Hanita Hashim Department of Computing, Faculty of Visual Art Communication and Computing, Universiti Selangor
  • Siti Hawa Mohd Yusoff Department of Computing, Faculty of Visual Art Communication and Computing, Universiti Selangor
  • Zuraini Ayop Department of Computing, Faculty of Visual Art Communication and Computing, Universiti Selangor
  • Shahida Abd.Latif Department of Computing, Faculty of Visual Art Communication and Computing, Universiti Selangor
  • Che Manisah Mohd Kasim Faculty of Communication, Visual Art and Computing, University Selangor, Malaysia
Keywords: Fertility Rate, Infant, Maternal Death, Montality Rate, Regression

Abstract

Abstract: Infant mortality is the death of an infant before his or her first birthday. WHO, 2020 stated that all over the world the number of children died is 2.4 million. There are 117 data that is related to infant mortality that have been included in this study. The aim of this research is to estimate the number of infant mortality by modeling regression between maternal death, fertility rate, and adolescent birth rate. The method that is being used in this study is multiple linear regression. Multiple regression is a regression model with multiple independent variables the independent variables are the number of maternal deaths, fertility rate, and adolescent birth rate while the dependent variable is the number of infant mortality. The analysis was done to study the relationship between the number of infant mortality, maternal death, fertility rate, and adolescent birth rate. Graphical presentations and numerical analysis prove the assumptions of multiple linear regression. The strength of the relationship was tested by using the Pearson Correlation Coefficient. The coefficient of determination is used to determine the value of the proportion of the total variation in infant mortality due to maternal death, fertility rate, and adolescent birth rate. Other than that this study also performed the basic regression diagnostic. This study concludes whether the model is suitable for all the variables used or not.

 

References

Adetoro, C. Amoo, E. (2018). A Statistical Analysis of Child Mortality: Evidence from Nigeria. Journal of Demography and Social Statistics, 1(March 2014), 110-120.
Akinwande, M. Ibrahim, A. Ibrahim, A. (2019). Analyzing infant and child (under-five) mortality in Zaria: A regression analysis approach. African Research Review, 10(3), 72.
Bhatt, C. Beck-Sague, C. (2018). Medicaid expansion and infant mortality in the United States. American Journal of Public Health, 108(4), 565-567.
Cohen, P., West, S. G., & Aiken, L. S. (2017). Applied multiple regression/correlation analysis for the behavioral sciences. Psychology press.
Daoud, J. I. (2017, December). Multicollinearity and regression analysis. In Journal of Physics: Conference Series (Vol. 949, No. 1, p. 012009). IOP Publishing.
Ely, D. M., & Driscoll, A. K. (2019). Infant mortality in the United States, 2019: data from the period linked birth/infant death file.
Fitrianto, A. Hanafi, I. Chui, T. (2016). Modeling Asia's Child Mortality Rate: A Thinking of Human Development in Asia. Procedia Economics and Finance, 35(October 2015), 249-255.
Fox, J. (2019). Regression diagnostics: An introduction. Sage publications.
Geruso, M., & Spears, D. (2018). Heat, humidity, and infant mortality in the developing world (No. w24870). National Bureau of Economic Research.
Maniruzzaman, M. Suri, H. Kumar, N. et al. (2018). Risk factors of neonatal mortality and child mortality in Bangladesh. Journal of Global Health, 8(1).
Mathews, T. J., & Driscoll, A. K. (2017). Trends in infant mortality in the United States, 2005-2014.
Olive, D. J. (2017). Multiple linear regression. In Linear regression (pp. 17-83). Springer, Cham.
Pena, R. Liljestrand, J. Zelaya, E. et al. (1999). Fertility and infant mortality trends in Nicaragua 1964-1993. The role of women's education. Journal of Epidemiology and Community Health, 53(3), 132-137.
Pena, R. Wall, S. Persson, L. (2000). The effect of poverty, social inequity, and maternal education on infant mortality in Nicaragua, 1988-1993. American Journal of Public Health, 90(1), 64-69.
Sarstedt, M., & Mooi, E. (2019). Regression analysis. In A Concise Guide to Market Research (pp. 209-256). Springer, Berlin, Heidelberg.
Subramaniam, T., Loganathan, N., Yerushalmi, E., Devadason, E. S., & Majid, M. (2018). Determinants of infant mortality in older ASEAN economies. Social Indicators Research, 136(1), 397-415.
Tang, C. F. (2019). Determinants of infant mortality rate in Malaysia: evidence from dynamic panel data study. Journal of Health Management, 21(4), 443-450.
Uddin, J. Hossain, Z. Ullah, M. (2019). Quantitative Methods in Demographics CHILD MORTALITY IN A DEVELOPING COUNTRY: Introduction. Journal of Applied Quantitative Methods, 4(3), 270-283.
UN Inter-Agency Group for Child Mortality Estimation, UNICEF, WHO, et al. (2020).
Levels & Trends in Child Mortality Estimation Child Mortality. Un Ig
Published
2023-12-31
How to Cite
Abd Wahab, Y. A., Hashim, H., Mohd Yusoff, S. H., Ayop, Z., Abd.Latif, S., & Mohd Kasim, C. M. (2023). A A Statistical Analysis of the Number of Infant Mortality in Peninsular Malaysia. Selangor Science & Technology Review (SeSTeR), 7(2), PREPRINT. Retrieved from https://sester.journals.unisel.edu.my/ojs/index.php/sester/article/view/326
Issue
Vol 7 No 2 (2023): Diversity and Inclusion of Digital Technology in Business, Community and Economic Development
Section
Articles in English

All materials contained within this journal are protected by Intellectual Property Corporation of Malaysia, Copyright Act 1987 and may not be reproduced, distributed, transmitted, displayed, published, or
broadcast without the prior, express written permission of Centre for Graduate Studies, Universiti Selangor, Malaysia. You may not alter or remove any copyright or other notice from copies of this content.