Ordinal Logistic Regression Model: An Application to Pregnancy Outcomes | Science Publications

Journal of Mathematics and Statistics

A. A. Adepoju¹  K. A. Adeleke¹ 

关键词: Ordinal logistics;    regression model;    pregnancy outcome;    categorical data;    proportional odds;   

DOI  :  10.3844/jmssp.2010.279.285

学科分类：社会科学、人文和艺术（综合）

来源: Science Publications

【 摘 要 】

Problem statement: This research aimed at modeling a categorical response i.e., pregnancy outcome in terms of some predictors, determines the goodness of fit as well as validity of the assumptions and selecting an appropriate and more parsimonious model thereby proffered useful suggestions and recommendations. Approach: An ordinal logistic regression model was used as a tool to model the three major factors viz., environmental (previous cesareans, service availability), behavioral (antenatal care, diseases) and demographic (maternal age, marital status and weight) that affected the outcomes of pregnancies (livebirth, stillbirth and abortion). Results: The fit, of the model was illustrated with data obtained from records of 100 patients at Ijebu-Ode, State Hospital in Nigeria. The tested model showed good fit and performed differently depending on categorization of outcome, adequacy in relation to assumptions, goodness of fit and parsimony. We however see that weight and diseases increase the likelihood of favoring a higher category i.e., (livebirth), while medical service availability, marital status age, antenatal and previous cesareans reduce the likelihood/chance of having stillbirth. Conclusion/Recommendations: The odds of being in either of these categories i.e., livebirth or stillbirth showed that women with baby

【 授权许可】

Unknown