Modelling fertility levels in Nigeria using Generalized Poisson regression-based approach
| Autor: | Temesgen Zewotir, Delia North, Lateef O. Amusa, Jecinta U. Ibeji |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Multidisciplinary
media_common.quotation_subject interaction effect Negative binomial distribution Fertility Regression analysis Poisson distribution Poisson regression symbols.namesake Generalized Poisson regression Standard error Negative Binomial regression Statistics symbols lcsh:Q lcsh:Science Children ever born media_common Statistical hypothesis testing Count data Mathematics |
| Zdroj: | Scientific African, Vol 9, Iss, Pp e00494-(2020) |
| ISSN: | 2468-2276 |
| Popis: | The rapid increase in total children ever born without a proportionate growth in the Nigerian economy has been a major concern. The total children ever born, being a count data, requires applying an appropriate regression model. Poisson distribution is the ideal distribution to describe this data, but it is deficient due to equality of variance and mean. This deficiency results in under/over-dispersion and the estimation of standard errors will be biased rendering the test statistics incorrect. This study aimed to model count data with the application of total children ever born using a Negative Binomial and Generalized Poisson regression. The Nigeria Demographic and Health Survey 2013 data of women within the age of 15–49 years were used. A comparison of the three models revealed that Generalized Poisson regression is the appropriate model to correct for under/over-dispersion with age of household head (P |
| Databáze: | OpenAIRE |
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