Version 1
: Received: 3 August 2019 / Approved: 5 August 2019 / Online: 5 August 2019 (14:36:49 CEST)
How to cite:
Adenomon, M.O.; Anikweze, E.C. On the Trends of Registered Birth and Death Rates in Nigeria: Evidence from Generalized Linear Models. Preprints2019, 2019080064. https://doi.org/10.20944/preprints201908.0064.v1.
Adenomon, M.O.; Anikweze, E.C. On the Trends of Registered Birth and Death Rates in Nigeria: Evidence from Generalized Linear Models. Preprints 2019, 2019080064. https://doi.org/10.20944/preprints201908.0064.v1.
Cite as:
Adenomon, M.O.; Anikweze, E.C. On the Trends of Registered Birth and Death Rates in Nigeria: Evidence from Generalized Linear Models. Preprints2019, 2019080064. https://doi.org/10.20944/preprints201908.0064.v1.
Adenomon, M.O.; Anikweze, E.C. On the Trends of Registered Birth and Death Rates in Nigeria: Evidence from Generalized Linear Models. Preprints 2019, 2019080064. https://doi.org/10.20944/preprints201908.0064.v1.
Abstract
This study investigated the trends of registered Death and Birth in Nigeria using Generalized Linear Models. Annual data on Death and Birth was collected from National Population Commission for the period of 2004 to 2017. The Natural increase calculated revealed a positive trend in the natural increase in Nigeria from 2004 to 2017. Evidence from summary statistics revealed some level of over dispersion (variance > mean). This study explored Poisson Regression Models and Negative Binomial Regression Models using two links (identity and log). The results revealed a positive increase in registration of birth and death rates in Nigeria and among the competing the models, Negative Binomial regression model with identity link emerged as the best model for modeling birth and death rates registration in Nigeria. Data on numbers of deaths and causes of death are essential if countries are to determine priorities, formulate and monitor policies for public health care as well as other government policies that may be based on such data
Keywords
birth; death; trends; generalized linear models (GLMs); poisson; negative binomial
Subject
MATHEMATICS & COMPUTER SCIENCE, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
