Probability Model for Human Fertility Behavior: Straddling Birth Interval Under Realistic Assumptions
American Journal of Theoretical and Applied Statistics
Volume 4, Issue 6, November 2015, Pages: 576-580
Received: Oct. 31, 2015; Accepted: Nov. 9, 2015; Published: Nov. 26, 2015
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Author
Ajay Shankar Singh, Department of Agricultural Economics & Management, University of Swaziland, Luyengo, Swaziland
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Abstract
Fertility analysis is important in understanding past, current and future trends of population size, Composition and growth. Information on fertility levels, patterns and trends experienced by a country is important for socio-economic planning, monitoring and evaluating programs. In recent years the study of birth intervals has acquired importance because of its relationships to fertility. The data on straddling birth interval, defined as a closed birth interval that straddles the survey date, is easy to obtain more accurately, though the collection of data requires retrospective as well as prospective surveys. This type of interval is useful for the study of reproduction of subsequent fecund women of a particular age group. In this paper, a probability distribution for the straddling birth interval regardless of parity has been derived by taking into account that different proportion of females are exposed to the risk of conception at different point of time. In this derived model, fecundability (λ) has been considered to be constant over the study period. The duration of time from the point of termination of PPA to the state of exposure has been taken as random variable (µ) which follows exponential distribution. The maximum likelihood estimation technique has been used for the estimation of parameter (λ) & (µ) through derived model.
Keywords
Probability Model, Fecundability, Birth Interval, Post Partum Amenorrhea (PPA), Contraceptive Practices
To cite this article
Ajay Shankar Singh, Probability Model for Human Fertility Behavior: Straddling Birth Interval Under Realistic Assumptions, American Journal of Theoretical and Applied Statistics. Vol. 4, No. 6, 2015, pp. 576-580. doi: 10.11648/j.ajtas.20150406.29
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Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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