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Multivariate Analysis of Infant and Child Mortality in Java and Bali

Published online by Cambridge University Press:  31 July 2008

Terence H. Hull
Demography Department, Australian National University, Canberra, Australia
Bhakta Gubhaju
Nepal Family Planning/Maternal and Child Health Project, Kathmandu, Nepal


Application of a multivariate analytical technique to the World Fertility Survey data for Java and Bali indicates that demographic variables, particularly the length of the preceding birth interval, are more important in explaining infant and child mortality differentials than are such social variables as education of parents or urban–rural residence. These findings are weakened to some extent by the lack of satisfactory data on household economic status which might have provided a better base for indirectly discerning the effects of nutrition and sanitation on mortality at young ages.

Research Article
Copyright © Cambridge University Press 1986

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Baker, R.J. & Nelder, J.A. (1978) The GLIM System: Release 3, Numerical Algorithms Group, Oxford.Google Scholar
Goodman, L. (1972) A modified multiple regression approach to the analysis of dichotomous variables. Am. sociol. Rev. 37, 38.Google Scholar
Hull, T.H. & Sunaryo, (1978) Levels and Trends of Infant and Child Mortality in Indonesia. Working Paper No. 15. Population Institute, Gadjah Mada University, Yogyakarta.Google Scholar
Kadarusman, J. (1982) Infant and Childhood Mortality Differentials in Java and Bali. MA thesis, Australian National University, Canberra.Google Scholar
Little, R.J.A. (1978) Generalized Linear Models for Cross-Classified Data from the WFS. Technical Bulletin No. 5/Tech. 834, World Fertility Survey, London.Google Scholar