The Prediction of the Maternal and Fetal Blood Lead Level via Generalized Linear Model
Generalized linear models (GLMs) are generalization of the linear regression models, which allow fitting regression models to response variable that is non normal and follows a general exponential family. The aim of this study is to encourage and initiate the application of GLMs to predict the mater...
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| Format: | Article |
| Language: | Arabic |
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College of Computer Science and Mathematics, University of Mosul
2009-06-01
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| Series: | المجلة العراقية للعلوم الاحصائية |
| Online Access: | https://stats.mosuljournals.com/article_30637_0ab8439f47fd3b66a78536117e4055cd.pdf |
| Summary: | Generalized linear models (GLMs) are generalization of the linear regression models, which allow fitting regression models to response variable that is non normal and follows a general exponential family. The aim of this study is to encourage and initiate the application of GLMs to predict the maternal and fetal blood lead level. The inverse Gaussian distribution with inverse quadratic link function is considered. Four main effects were significant in the prediction of the maternal blood lead level (pica, smoking of mother, dairy products intake of mother, calcium intake of mother), while in the prediction of the fetal blood lead level two main effects showed significance (dairy products intake of mother and hemoglobin of mother).
Keywords: Generalized linear models, Exponential family, Inverse Gaussian distribution, Link functions |
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| ISSN: | 1680-855X 2664-2956 |