Introduction The prevalence of end-stage renal disease has raised the need for renal replacement therapy over recent decades. Even though a kidney transplant offers an improved quality of life and lower cost of care than dialysis, graft failure is possible after transplantation. Hence, this study aimed to predict the risk of graft failure among post-transplant recipients in Ethiopia using the selected machine learning prediction models. Methodology The data was extracted from the retrospective cohort of kidney transplant recipients at the Ethiopian National Kidney Transplantation Center from September 2015 to February 2022. In response to the imbalanced nature of the data, we performed hyperparameter tuning, probability threshold moving, tree-based ensemble learning, stacking ensemble learning, and probability calibrations to improve the prediction results. Merit-based selected probabilistic (logistic regression, naive Bayes, and artificial neural network) and tree-based ensemble (random forest, bagged tree, and stochastic gradient boosting) models were applied. Model comparison was performed in terms of discrimination and calibration performance. The best-performing model was then used to predict the risk of graft failure. Results A total of 278 completed cases were analyzed, with 21 graft failures and 3 events per predictor. Of these, 74.8% are male, and 25.2% are female, with a median age of 37. From the comparison of models at the individual level, the bagged tree and random forest have top and equal discrimination performance (AUC-ROC = 0.84). In contrast, the random forest has the best calibration performance (brier score = 0.045). Under testing the individual model as a meta-learner for stacking ensemble learning, the result of stochastic gradient boosting as a meta-learner has the top discrimination (AUC-ROC = 0.88) and calibration (brier score = 0.048) performance. Regarding feature importance, chronic rejection, blood urea nitrogen, number of post-transplant admissions, phosphorus level, acute rejection, and urological complications are the top predictors of graft failure. Conclusions Bagging, boosting, and stacking, with probability calibration, are good choices for clinical risk predictions working on imbalanced data. The data-driven probability threshold is more beneficial than the natural threshold of 0.5 to improve the prediction result from imbalanced data. Integrating various techniques in a systematic framework is a smart strategy to improve prediction results from imbalanced data. It is recommended for clinical experts in kidney transplantation to use the final calibrated model as a decision support system to predict the risk of graft failure for individual patients.

Abstract:Marriage breakdown is a condition in which partners of a marital union cease to live together especially due to divorce or separation. The main objective of this study is identifying factors for marriage breakdown. To achieve this sample of 576 respondents was taken using stratified random sampling method, during March 2012. From descriptive statistics we have seen that about 41.7% of the first marriage was broken in Debre Birhan town. A series of statistical analysis have done: factors for marriage breakdown were analyzed using binary logistic regression and time to marriage breakdown was analyzed by Cox proportional hazard model. From the binary logistic regression we have seen that being infertile, marry at age of 12-18 years (early marriage), sexual incompatibility, unfaithfulness, absence of discussion and illiterate husbands are exposed to the risk of marriage break down. From the Cox proportional hazard model we have seen that; spouses who are infertile, marry b/n 12-18 years for females, too low (<4 years) or too high (>10 years) age gap, having different religion, sexual incompatibility and unfaithfulness leads to the shorter survival time of first marriage. Finally we have recommend that Spouses should have a habit of discussion, specially on sexual issue, youth should insure that they have the potential to pursue marriage its responsibility before coming to the institution. Awareness creation and counseling service should have given about the effect of early marriage, the importance of legal-marriage, impact of religion difference of spouses and gender equality.

Introduction Duration of breastfeeding is the length of the time that infants who were initially breastfed continue to receive breast milk until weaning. The duration of breastfeeding is important for a child's health, growth, and development. However, the duration of breastfeeding decreases from time to time and further leads children to be exposed to malnutrition (stunting, wasting, and weight loss). Children who did not get enough breastfeeding are also exposed to different diseases. Previous studies used a simple survival model and didn’t see the shared frailty model on the variable of interest. Therefore, the current study aimed to investigate the factors affecting the duration of breastfeeding among Ethiopian women of reproductive age with babies. Methods A cross-sectional study design was conducted on 15,400 women of childbearing age with babies in nine regional states and two city administrations. The data source for the analysis was the 2016 EDHS data. The Cox-proportional hazard model, AFT, and parametric shared frailty models were conducted for the current investigation. Weibull-gamma shared frailty model was in favor of others for current data analysis. Results Among the covariates, women living in urban area (Φ = 0.96; 95% CI; (0.94,0.97); p-value = 0.001), non-educated women(Φ = 1.03; 95% CI; (1.00,1.06); p-value = 0.039), primary educated women (Φ = 1.13; 95% CI; (1.11,1.15); p-value < 0.001), age of a child (Φ = 0.99; 95% CI; (0.76.0.99); p-value < 0.001) and non-smoker mothers (Φ = 1.60; 95% CI; (1.57, 1.63); p-value < 0.001),birth interval between 2–3 years(Φ = 1.02; 95% CI;(1.09, 1.25, p-value = 0.027), birth interval, > 3 years(Φ = 1.28; 95% CI; (1.06, 1.43); p-value < 0.01 significantly affected the duration of breastfeeding. The median survival time of breastfeeding of women of reproductive age with babies considered under study was 23.4 months. Clustering had a significant effect on the variable of interest. Conclusion Residence area, level of education, age of the child, smoking status of women, and birth interval of successive birth significantly affected the duration of breastfeeding in the current investigation. Hence, the health staff should conduct health-related education for young women, educated women, urban women, smoker women, and women with a shorter interval of birth to increase the women's attitude and awareness towards the use of long-duration of breastfeeding.

In order to ensure the achievement of organization's goals, it should create an atmosphere of commitment and cooperation for its employees through policies that facilitate employee satisfaction. The main objective of the study is identifying factors affecting employee's job satisfaction and supervisor performance at Debre Berhan University. In order to meet the objective of the study a sample of 272 employees have taken. And consecutive statistical methods have been used. Both descriptive and inferential group of statistical tools have been applied. The descriptive result of the study reveals that about 63.2% of the sampled employees have unsatisfied and the rest 36.8% of them have satisfied with the working condition of the university. From logistic regression analysis of job satisfaction it is evident that the way of promotion, encouragement of research work, accessibility of office, merit based job allocation, recognition for contributions, responding the need of home and facility of working materials have significant effect on employees job satisfaction at 5% level of significant. Multiple linear regression also shows that handles employees complaints, does not allow special privilege, availability of supervisor for staffs, being respectful, good leading skill, trust on clerk, and sense of responsibility have significant effect on the supervisor performance at 5% level of significance. Finally chi-square test of association of overall job satisfaction and overall supervisor performance shows that there is a strong association between job satisfaction and performance of immediate supervisors. from consecutive result of the study it is recommended that; the management of the university should improve the way of promotion for staffs based on the legislation of the university, there should be motivated encouragement and recognition for researchers so that scientific environment can be created in the compound, the university should also work hard to satisfy the need of staffs for home and the allocation of supervisors in different hierarchy should be merit based.