Computer Simulation in Human Population Studies by Bennett Dyke, Jean Walters MacCluer

By Bennett Dyke, Jean Walters MacCluer

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After the age of fifty, the probability of death during each year increases sharply and it goes on increasing until there is no one left to be at risk of dying. The differences between model lifetables by level of mortality are primarily differences in the probability of dying at each age, that is to say, the height of the probability curve. Differences 51 NANCY HOWELL between families of curves have to do with the rela­ tive distribution of mortality at different ages, in such matters as the slope of the decline during the early childhood years, the relative amount of in­ crease during the fifty-year-old decade as opposed to the sixty-year-old decade.

Population genetics and social anthropology, Cold Spring Harbor Symposia on Quantitative Biology 15: 401-408. 40 SIMULATION OF HUMAN POPULATIONS Kluckhohn, C. and D. Leighton 1962. The Navaho, Revised Edition. New York: Doubleday. MacCluer, J. W. 1967. Monte Carlo methods in human population genetics: a computer model incorpora­ ting age-specific birth and death rates, American Journal of Human Genetics 19: 303-312. MacCluer, J. W. 1968. D. dissertation, Univ. of Michigan. MacCluer, J. W. 1973.

Finding that there is a 30 year difference or a 10 year difference according to a method of estimating ages should cause us to doubt the method. Kung has been to fit a stable population model age distribution over the rank-order of ages that was collected in the field. The model chosen was selected on the basis of an estimate of completed family size, a judgment about the point in the rank-order of ages that separates those ten years old and younger from those older, and a guess about the level of mortality that one would find in a population like this one.

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