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Abstract
In this paper, multilevel logistic regression models are developed for examining the hierarchical effects of contraceptive use and its selected determinants in Oman using the 2008 Oman National Reproductive Health Survey (ONRHS). Comparison between single level and multilevel logistic regression models has been made to examine the plausibility of multilevel effects of contraceptive use. From the multilevel logistic regression model analysis, it was found that there is real multilevel variation among contraceptive users in Oman. The results indicate that a multilevel logistic regression model is the best fit over ordinary multiple logistic regression models. Generally, this study revealed that women’s age, education, number of living children and region of residence are important factors that affect contraceptive use in Oman. The effect of regional variation for age of women, education of women and number of living children further implies that there exists considerable differences in modern contraceptive use among regions, and a model with a random coefficient or slope is more appropriate to explain the regional variation than a model with fixed coefficients or without random effects. The study suggests that researchers should use multilevel models rather than traditional regression methods when their data structure is hierarchal.
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References
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- Raudenbush, S.W. and Bryk, A.S. Hierarchical Linear Models: Applications and Data Analysis Methods. Thousand Oaks, CA: Sage Publications, London, 2002.
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- Kreft, I. and De Leeuw, J. Introducing Multilevel Modeling. Sage Publications, London, 1998.
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- Bryk, A.S. and Raudenbush, S.W. Hierarchical Linear Models. Newbury Park, CA: Sage Publication, London, 1992.
- Al-Riyami, A., Abdel El Aty, M.A., Jaju, S., Morsi M., Al-Kharusi, H. and Al-Shekaili, W. Oman National Reproductive Health Survey. Muscat: Ministry of Health, Sultanate of Oman, 2008.
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- Khan, H.T.A. A hierarchical model of contraceptive use in urban and rural Bangladesh. Contraception, 1997, 55: 91-96.
- Khan, H.R. and Shaw, J.E.H. Multilevel Logistic regression analysis applied to binary contraceptive prevalence Data. J. Data Science, 2011, 9, 93-110.
- Kalam, E.M.N. and Khan, H.T.A. Modeling contraceptive prevalence in Bangladesh: A hierarchical approach. Asian Meta Centre, Research Paper Series, No. 21, 2002
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References
Snijders, T.A.B. and Bosker, R.J. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. Sage Publications, London, 1999.
Raudenbush, S.W. and Bryk, A.S. Hierarchical Linear Models: Applications and Data Analysis Methods. Thousand Oaks, CA: Sage Publications, London, 2002.
Goldstein, H. Multilevel Statistical Models. Edward Arnold: London, Halsted Press, New York, 1995.
Austin, P.C., Goel, V., van Walraven C. An introduction to multilevel regression models. Can J. Public Health, 2001, 92, 150-4.
Goldstein, H. Multilevel Models in Educational and Social Research. Griffin: London, Oxford University Press: London, 1987.
Goldstein, H. Performance Indicators in Education. Statistics in Society, D. Dorling and S. Simpson. Part VI, pp. 281-286, Arnold, London, 1999.
Hox, J.J. Multilevel Analysis: Techniques and Applications. Lawrence Erlbaum Associates, Inc., Mahwah, NJ, 2002.
Harttgen, K. and Misselhorn, M. A Multilevel Approach to Explain Child Mortality and Undernutrition in South Asia and Sub-Saharan Africa. Discussion Paper, Ibero-America Institute for Economic Research, No. 152, 2006.
Kreft, I. and De Leeuw, J. Introducing Multilevel Modeling. Sage Publications, London, 1998.
Goldstein, H. Nonlinear multilevel models, with an application to discrete response data. Biometrika, 1991, 78(1), 45-51.
Bryk, A.S. and Raudenbush, S.W. Hierarchical Linear Models. Newbury Park, CA: Sage Publication, London, 1992.
Al-Riyami, A., Abdel El Aty, M.A., Jaju, S., Morsi M., Al-Kharusi, H. and Al-Shekaili, W. Oman National Reproductive Health Survey. Muscat: Ministry of Health, Sultanate of Oman, 2008.
Filmer, D., Pritchett and L.H. Estimating wealth effects without expenditure data or tears: An Application to Educational Enrolments in States of India. Demography, 2001, 38(1), 115-132.
Khan, H.T.A. A hierarchical model of contraceptive use in urban and rural Bangladesh. Contraception, 1997, 55: 91-96.
Khan, H.R. and Shaw, J.E.H. Multilevel Logistic regression analysis applied to binary contraceptive prevalence Data. J. Data Science, 2011, 9, 93-110.
Kalam, E.M.N. and Khan, H.T.A. Modeling contraceptive prevalence in Bangladesh: A hierarchical approach. Asian Meta Centre, Research Paper Series, No. 21, 2002
Ferede, T. Multilevel modeling model of modern contraceptive use among rural and urban population of Ethiopia. Am. J. Math. Stat., 2013, 3(1), 1-16.
Goldstein, H. Multilevel Statistical Models. Edward Arnold, London, 2003.