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Thesis Title IDENTIFYING RISK FACTORS OF CESAREAN SECTION USING FACTOR SELECTION METHODS
Student Name Sughra Sarwar
Registration No. 2013-GDTG(G)-016106
Session 2019-2021
Program M.Phil
Faculty Science
Department Department of Statistics
Supervisor Dr. Maryam Sadiq
Abstract The present study is conducted to compare the classical method (standard logistic) with an innovative method, ”a hybrid of relaxed lasso and ridge regression,” in which properties of relax lasso and ridge regression are combined. We also illustrate the efficacy of the proposed approach using both simulated and real-life data. The results suggest that HRLR-logistic selects the best subsets compared to standard logistic. In addition, the study identifies the elements that contribute to cesarean section in Pakistan. We find that education, socio-economic status, utilization/availability of health services, and mother’s age are remarkable factors associated with cesarean section.
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