Multinomial Logistic for Modeling Contraceptive Use by Women in Kenya
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Contraceptive use is viewed as a safe and affordable way to halt rapid population growth and reduce maternal and infant mortality. However, not all contraceptives are appropriate for every woman. To predict the probabilities of more than two different possible contraceptive methods, binary logit models cannot be used rather Multinomial Logistic Regression (MLR) model. However, the complexity of the theory, as well as the complexity in interpreting analysis and results of this model is the reason behind its little research. This book provides a clear insight as far as both the theory and applic...
Contraceptive use is viewed as a safe and affordable way to halt rapid population growth and reduce maternal and infant mortality. However, not all contraceptives are appropriate for every woman. To predict the probabilities of more than two different possible contraceptive methods, binary logit models cannot be used rather Multinomial Logistic Regression (MLR) model. However, the complexity of the theory, as well as the complexity in interpreting analysis and results of this model is the reason behind its little research. This book provides a clear insight as far as both the theory and application part of this baseline model is concerned. It will be very helpful especially to policymakers who wish to predict the contraceptive method different women may use, reasons behind using this method and provide safe family planning methods to curb population pressure. Similarly, researchers will have access to an enriched literature on MLR application.
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