ORDINAL REGRESSION FOR MODELLING THE FAMILY WELL-BEING AMONG THE MALAYSIANS

Noor Azlin  Muhammad Sapri; Kamarulzaman  Ibrahim; Mohd Aftar  Abu Bakar; Noratiqah  Mohd Ariff

doi:10.24200/jonus.vol6iss2pp424-447

Noor Azlin Muhammad Sapri Research Division on Population and Family, National Population and Family Development Board, 50712 Kuala Lumpur, Malaysia. https://orcid.org/0000-0001-6920-6750
Kamarulzaman Ibrahim Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia. https://orcid.org/0000-0002-2309-3663
Mohd Aftar Abu Bakar Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia. https://orcid.org/0000-0002-3009-6168
Noratiqah Mohd Ariff Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia. https://orcid.org/0000-0001-5538-1339

DOI: https://doi.org/10.24200/jonus.vol6iss2pp424-447

Abstract

Background and Purpose: Understanding factors which affect the level of family well-being is important as it contributes to effective decision making among the policymakers to improve the family lives as well as to strengthen the family institution. Accordingly, this line of research is gaining attention. This study develops an ordinal regression model which identifies demographic, economic and social factors that are significant in explaining the status of family well-being.

Methodology: Data involving 2,808 respondents from a nationwide survey conducted by the National Population and Family Development Board of Malaysia in 2011 were used in this study. Ordinal regression model was implemented to describe the three levels of family well-being.

Findings: The national survey reported that high level of family well-being was experienced by 76.3 per cent of the respondents, followed by moderate (18.4%) and low (5.3%). The fitted ordinal regression model found that ethnic background, family relationship, community relationship, health and safety levels, economic situation of the family, religious practice, housing, and environment are significantly related to family well-being. Meanwhile, it was found that the level of income is not a significant factor in determining the level of family well-being.

Contributions: There are a limited number of studies on the application of ordinal regression for modelling the level of family well-being, particularly with covariates involving the demographic and social characteristics of the respondents. This study fills in the gap in the literature where the ordinal regression model provides useful information for policymakers to enhance the status of family well-being in Malaysia via various policy initiatives.

Keywords: Family well-being, Ordinal Regression Model, ordinal data, Proportional Odds Model.

Cite as: Muhammad Sapri, N. A., Ibrahim, K., Abu Bakar, M. A., & Mohd Ariff, N. (2021). Ordinal regression for modelling the family well-being among the Malaysians. Journal of Nusantara Studies, 6(2), 424-447. http://dx.doi.org/10.24200/jonus.vol6iss2pp424-447

Author Biographies

Noor Azlin Muhammad Sapri, Research Division on Population and Family, National Population and Family Development Board, 50712 Kuala Lumpur, Malaysia.

NOOR AZLIN MUHAMMAD SAPRI is a Statistician at the National Population and Family Development Board (NPFDB). She received her B.S. in Statistics and M.S. in Statistics from the Universiti Kebangsaan Malaysia in 2003 and 2004, respectively. Her research area is mainly on the Malaysian population and family.

Kamarulzaman Ibrahim, Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

KAMARULZAMAN IBRAHIM is a Professor in Statistics at the Universiti Kebangsaan Malaysia. He received his B.S. in Mathematics from the College of Charleston, S.C, USA, in 1984. In 1986, he obtained the M.A. in Statistics from the Mississippi State University, Starkville, USA. Then in 1995, he earned a Ph.D. in the area of Applied Statistics from the University of Newcastle upon Tyne, U.K. Since 1986, he was a lecturer in Statistics Program, School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, and he was promoted as a Professor in Statistics in 2011. His research interest includes, among others, statistical modelling and Bayesian statistics. Previously, he is the President for Malaysia Institute of Statistics.

Mohd Aftar Abu Bakar, Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

MOHD AFTAR ABU BAKAR is a Senior Lecturer at the Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia. He received his B.S. degree in Industrial Mathematics from the Universiti Teknologi Malaysia in 2006. In 2008, he received his M.S. degree in Mathematics from the same university. He then obtained his Ph.D. in Mathematics from the University of Adelaide, Australia in 2016. His research interests include time series analysis, statistical modelling, data science, signal processing and machine learning.

Noratiqah Mohd Ariff, Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

NORATIQAH MOHD ARIFF is a Senior Lecturer at the Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia. Dr. Noratiqah joined Universiti Kebangsaan Malaysia in 2009. She received her B.S. degree in Mathematics and M.S. degree in Mathematics from the Universiti Teknologi Malaysia in 2008 and 2010, respectively. She then obtained her Ph.D. in Statistics from the Universiti Kebangsaan Malaysia in 2014. Her research is in the area of computational statistics, data science and statistical modelling.

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