Browsing by Author "Sesay, Regina Baby"

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A Logistic Regression Model to Identify Factors Influencing Secondary School Students’ University Attendance Decision in the Southern Part of Sierra Leone
(Federal Reserve Bank of St. Louis, 2021) Sesay, Regina Baby
University education does not only increase earnings by providing skills that increase the chance of employment opportunities, but also promotes the economic growth of the country concern.For a developing country like Sierra Leone, a step to attain university education is a step towards moving away from poverty.It is therefore the desire of each and every parent to see their children through university level education.However, there are some unavoidable factors that may influence the ability and desire of provincial secondary (high) school students to further their education to university level.In Sierra Leone today, despite the increasing number of school dropouts, no clear-cut research has been carried out to address this great issue of concern.This research work, therefore, used a binary logistic regression modelling technique to identify the main factors influencing students' decision to attend a university of their choice after secondary (or high) school education.For this purpose, a stratified random sampling method was employed to select 363 respondents proportionately from each of the secondary schools in the Mokonde community, Korie chiefdom, Moyamba District, southern part of Sierra Leone.Data were collected from the selected respondents using structured questionnaires.To further ascertain the appropriateness of the chosen binary logistic regression model, two additional regression models, the proportional odd ordinal logistic regression model and the unconstrained partial proportional odd ordinal logistic regression model were also used in the analysis.However, statistical tests showed that the chosen binary logistic regression model outperformed the two ordinal regression models.Based on the result of the empirical analysis, the gender of the secondary (high) school student; the father's income level; the mother's income level; the annual average score and the number of study hours are the main factors influencing student's university attendance decision in the study area.Male secondary (or high) school students are more likely to attend university than their female counterparts.High school students whose fathers are on a high level income scale are more likely to attend university than those whose fathers are on the low level income scale.Also, the higher the average score of the secondary school student the greater the possibility of the student to enter university and above all, the more hours the student spends on studying his or her academic work, the greater the possibility for the student to enter university.
Application of Adjacent Categories and Continuation Ratio Logit Models in Determining Factors Influencing Malnutrition in Children Living in the Eastern Part of Freetown, Sierra Leone.
(2022) Sesay, Regina Baby
Malnutrition in children under five years of age remains a problem in many part of the world especially in Africa of which Sierra Leone is not an exception.In Sierra Leone, the magnitude of stunting, underweight and wasting in children less than five years increases tremendously in the rural areas, especially in the raining season.Child growth is nationally and internationally recognized as a principal indicator of the nutritional and health status of the populations of a country.Therefore, identifying the main factors associated with childhood malnutrition can help to inform and advice both Government and other national health agencies to implement policies that will help to alleviate or minimize the incidence in the country.No research have been conducted especially after the 5 years Sierra Leone rebel war, to particularly investigate the factors influencing malnutrition in under-five children living in this part of the country.This research work, therefore, aimed to identify the main factors influencing malnutrition in under-five children living in the eastern part of the capital city of Sierra Leone.A random sampling method was used to collect 500 observations from the study area.An ordinal logistic regression modelling techniques that involved the proportional odds; the nonproportional odds adjacent categories and the non-proportional odds forward continuation ratio logit models were used in the empirical analysis.Statistical tests showed that, the nonproportional odds adjacent category model outperformed both the proportional odds and the non-proportional odds continuation ratio models.Based on the empirical evidence, the mother's age, the family income level and the number of postnatal hospital visits were the main factors influencing the malnutrition status of the under-five children living the study area.The child's age and the child's feeding status were also found to be significant determinants of under-five children malnutrition status.Malnutrition increases in under-five children from younger mothers, as compared to under-five children from older mothers.The more frequent, the number of post-natal hospital visit, the lower the malnutrition status of the under-five children.Similarly, increase in family income will reduce the incidence of malnutrition in under-five children.Also, malnutrition increases in older children as compared to younger children.Finally, the higher the quality and frequency of child's feed, the lower the incidence of malnutrition in under-five children.
Determinants of Under-five Child Mortality in the East End of Freetown, Sierra Leone: A Hurdle Negative Binomial Modelling Approach
(SAGE Publications, 2026-03-01) Sesay, Regina Baby
**Objective:** To identify the main determinants of under-five child mortality in the eastern region of Sierra Leone's capital using the most appropriate count regression modeling approach. **Introduction:** Sierra Leone has seen rising under-five mortality, especially in densely populated areas like the eastern part of its capital. Understanding the main factors associated with such under-five mortality is vital for guiding healthcare policies and promoting appropriate interventions to reduce its risk. **Methods:** In this research, 755 observations were randomly collected from the residents of the study area through interviews and questionnaires. This paper fitted several count models: Poisson and Generalized Poisson regressions, Zero-inflated Poisson regression, Negative binomial regression, and the Hurdle Negative Binomial regression. To compare the models based on how well they fit the count data at hand, this research used the Vuong non-nested test, the Akaike Information Criterion, the Bayesian Information Criterion, and a graphical method called the hanging rootogram. **Results:** The hurdle negative binomial regression model is identified as the preferred model that best fits the data used in this study. The best-fitting model showed that the mother's age, mosquito net use, family income, and child feeding practices are the main determinants. **Conclusion:** This study revealed that a younger maternal age, a reduction in family income, a decline in both the frequency and quality of child feeding, and a decrease in the number of times a child sleeps under a mosquito net were each associated with a heightened risk of mortality among children under five in the study area.