Fitting age-specific fertility with the Makeham curve.
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Life tables by sex for the Netherlands for 1983 and 1982-1983 are presented. Differences between the tables as a result of using different ways of calculating the mortality quotients are explained. "The quotients in the life tables for 1983 are based on the registration of deaths in that year as well as the distribution of the population on January 1st and December 31st 1983 by age and sex.... Both the number of deaths in 1982 and that in 1983 are used to compute the mortality quotients for the life tables 1982/1983." (summary in ENG)
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A general framework for the analysis of the complex determinants of infant and child mortality in developing countries is presented. "This framework distinguishes five types of variables: the discriminatory, independent, intermediate, determinant and dependent variables which correspond to the different levels of analysis and explanation. A non exhaustive presentation is made of the variables involved in each group and of their main relations. Finally, the main effects of the determinants analysed in [selected] case studies concerning the developing countries...are discussed on the basis of the suggested framework of analysis." The case studies are published in Cahiers ORSTOM: Serie Sciences Humaines, Vol. 20, No. 2, 1984. (summary in ENG, SPA)
"This paper describes the historical evolution of five populations and analyzes the circumstances under which data on maternal and paternal orphanhood of couples at the moment of marriage were collected and compiled." The data, which concern historical populations in Mexico, Chile, Peru, Brazil, and Argentina, are used to construct life tables for male and female adults. Consideration is given to mortality differentials by sex. (summary in ENG)
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"The World Fertility Survey carried out cross-sectional probability surveys of fertility in more than 40 developing countries between 1972 and 1984. Statistical issues in regression analysis of the data are reviewed, including treatment of interactions, the selection of regressor variables, and appropriate linear models for rate variables. Similar issues arise in many other applications of regression to observational data."