Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Ordinal logistic regression model: an application to pregnancy outcomes

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 recom...

Full description

Saved in:
Bibliographic Details
Format: Article
Published: 2010
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000njm a2000000a 4500
001 oai:repository.ui.edu.ng:123456789/7647
042 |a dc 
720 |a Adeleke, K.A.  |e author 
720 |a Adepoju, A.A.  |e author 
260 |c 2010 
520 |a 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’s weight less than 2.5 kg are 18.4 times more likely to have had a livebirth than are women with history of babies 2.5 kg. Age (older age and middle aged) women are one halve (1.5) more likely to occur than lower aged women, likewise is antenatal, (high parity and low parity) are more likely to occur 1.5 times than nullipara. 
024 8 |a 1549-3644 
024 8 |a ui_art_adeleke_ordinal_2010 
024 8 |a Journal of Mathematics and Statistics 6(3) 2010. Pp.279-285 
024 8 |a http://ir.library.ui.edu.ng/handle/123456789/7647 
653 |a Ordinal logistics 
653 |a Regression model 
653 |a Pregnancy outcome 
653 |a Categorical data| 
653 |a Proportional odds 
245 0 0 |a Ordinal logistic regression model: an application to pregnancy outcomes