Generalized Linear Models to Investigate Cyclic Trends

Tibor András Nyári ()
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Tibor András Nyári: University of Szeged, Department of Medical Physics and Informatics

A chapter in Trends in Biomathematics: Modeling Cells, Flows, Epidemics, and the Environment, 2020, pp 335-341 from Springer

Abstract: Abstract The aim of this study was to illustrate the usage of generalized linear models in analyzing seasonal variation without and with confounder variable. Monthly data on the numbers of live births and infant deaths were obtained from the Hungarian nationwide population register during the 22 year interval between 1 January 1996 and 31 December 2017. Cyclic trends were investigated by Poisson regression. Significant double-peak (May and November) trends were found in mortality rates for infant deaths. However, a single-peak in December was observed in low birthweight mortality after adjusting seasonality to birthweight. These results illustrate the importance of generalized linear models in analyzing seasonal variation.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-46306-9_20

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DOI: 10.1007/978-3-030-46306-9_20

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