Contraceptive ever-use among women of reproductive age in Northern Ghana: a comparative analysis of logistic regression, LASSO penalised regression, and random forest machine learning approaches
Joseph Lasong, Mavis Kala, Torjim Salifu, Yula Salifu · 2026
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Description
Joseph Lasong, Mavis Kala, Torjim Salifu, and Yula Salifu studied contraceptive use among women in northern Ghana. Their paper, published in two thousand twenty-six, asks why use stays low even when women know about birth control. They compare three ways to predict who has ever used it.
The survey covered four hundred fourteen women aged fifteen to forty-nine at three public health sites in Tamale. Random forest, a machine learning method, sorted users from non-users best. Standard regression still gave the clearest links, tied to views, schooling, number of births, and advice from health workers. The authors say both tools have value, for prediction and for clear explanations.
Catalog record
| CREATOR | Joseph Lasong, Mavis Kala, Torjim Salifu, Yula Salifu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 50 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |