Dr. Hellen Waititu

Position: Head of Department; Lecturer

Department: Mathematics and Actuarial Sciences

Specialisation: Survival Analysis, Biostatistics

Email: hwaititu@cuea.edu

Dr. Hellen Waititu holds a PhD in Biostatistics from Moi University's School of Sciences and Aerospace Studies, Department of Mathematics, Physics, and Computing (2016-2021), a Master of Science in Statistics from Kenyatta University, and a Bachelor of Education (Double Mathematics) from the Catholic University of Eastern Africa (1996-2000). She has served as Head of the Mathematics and Actuarial Science Department at CUEA since January 2022 and has also served as Examination Coordinator in the same department. She is skilled in data analysis using R, Python and SPSS. Her research interests include biostatistics, data analysis, machine learning, and curriculum development.

Authors: Nsabimana, F., Waititu, H., & Nyakundi, C. Journal: Asian Journal of Probability and Statistics 24(1), 45-61. https://doi.org/

A COPULA-BASED APPROACH FOR MODELING THE DEPENDENCE BETWEEN INFLATION AND EXCHANGE RATE IN KENYA Authors: Tracy, K., Waititu, H., & Sewe, S. Journal: Asian Journal of Probability and Statistics 18(4), 59-84. https://doi.org/

NONPARAMETRIC ESTIMATION OF ERROR VARIANCE UNDER SIMPLE RANDOM SAMPLING WITHOUT REPLACEMENT Authors: Odhiambo, V., Waititu, H., & Onwando, N. C. Journal: International Journal of Mathematics and Computer Research

EVALUATING THE ROLE OF MATERNAL INCOME IN MEDIATING THE EFFECT OF MOTHER'S EDUCATION ON UNDER-FIVE CHILD MORTALITY IN KENYA Authors: Mundia, I., Waititu, H., Owuor, N., & Sewe, S. Journal: Asian Journal of Probability and Statistics 18(3), 10-22. https://doi.org/

ANALYSIS OF BALANCED RANDOM SURVIVAL FOREST USING DIFFERENT SPLITTING RULES: APPLICATION ON CHILD MORTALITY Authors: Waititu, H. W., Koskei, J. K., & Onyango, N. O. Journal: International Journal of Statistics and Applications 11(2), 37-49. https://doi.org/ 2020

DETERMINANTS OF UNDER-FIVE CHILD MORTALITY FROM KDHS DATA: A BALANCED RANDOM SURVIVAL FORESTS (BRSF) TECHNIQUE Authors: Waititu, H. W., Koskei, J. K., & Onyango, N. O. Journal: International Journal of Statistics and Applications 10(5), 118-130. https://doi.org/

IMPROVED BALANCED RANDOM SURVIVAL FOREST FOR THE ANALYSIS OF RIGHT CENSORED DATA: APPLICATION IN UNDER-FIVE MORTALITY Authors: Waititu, H. W. Journal: PhD Thesis, Moi University Doctoral Dissertation 2019

APPLICATION OF COX PH MODEL ON BROILERS IN LA NYEVU POULTRY FARM IN KALOLENI SUB-COUNTY; A SURVIVAL ANALYSIS CASE STUDY Authors: Ngolo, N., Okuto, E., & Waititu, H. Journal: Bulletin of Mathematics and Statistics Research 7(3)

NON-PARAMETRIC VARIANCE ESTIMATION USING DONOR IMPUTATION METHOD Authors: Waititu, H. W., & Njenga, E. Journal: American Journal of Theoretical and Applied Statistics 5(5), 252-259. https://doi.org/

Research interests: Survival Analysis; Random Survival Forests; Child Mortality Analysis; Statistical Modeling; Copula GARCH Models; Nonparametric Estimation; Economic Statistics; Health Statistics; Dr. Hellen Waititu is an accomplished statistician whose research has made significant contributions to survival analysis and child mortality studies. Her doctoral work on improved balanced random survival forests has advanced statistical methodologies for analyzing right-censored data, with particular applications in understanding under-five child mortality in Kenya.; Her expertise in Copula GARCH modeling has provided valuable insights into the dependency structures between economic variables, including the relationship between inflation and exchange rates. This work has important implications for economic policy and forecasting.; Dr. Waititu's research extends to nonparametric estimation methods and their applications in various fields. Her work on evaluating maternal factors affecting child mortality has contributed to public health policy discussions and interventions aimed at reducing child mortality rates in Kenya.

Nsabimana, F., Waititu, H., & Nyakundi, C. (2023). Modeling dependence using Copula GARCH. Asian Journal of Probability and Statistics. https://doi.org/10.9734/ajpas/2023/v24i1517

Tracy, K., Waititu, H., & Sewe, S. (2022). A copula-based approach for modeling the dependence between inflation and exchange rate in Kenya. Asian Journal of Probability and Statistics. https://doi.org/10.9734/ajpas/2022/v18i430457

Odhiambo, V., Waititu, H., & Onwando, N. C. (2022). Nonparametric estimation of error variance under simple random sampling without replacement. International Journal of Mathematics and Computer Research. https://doi.org/10.47191/ijmcr/v10i10.02

Mundia, I., Waititu, H., Owuor, N., & Sewe, S. (2022). Evaluating the role of maternal income in mediating the effect of mother's education on under-five child mortality in Kenya. Asian Journal of Probability and Statistics. https://doi.org/10.9734/ajpas/2022/v18i330448

Waititu, D. H. (2022). A Copula-Based Approach for Modelling the Dependence between Inflation and Exchange Rate in Kenya. Asian Journal of Probability and Statistics. https://doi.org/10.9734/ajpas/2022/v18i430457

Waititu, H. W. (2021). Improved balanced random survival forest for the analysis of right censored data: Application in under-five mortality. Moi University.

Waititu, H. W., Koskei, J. K., & Onyango, N. O. (2021). Analysis of balanced random survival forest using different splitting rules: Application on child mortality. International Journal of Statistics and Applications.

Waititu, H. W., Koskei, J. K., & Onyango, N. O. (2020). Determinants of under-five child mortality from KDHS data: A balanced random survival forests (BRSF) technique. International Journal of Statistics and Applications.

Ngolo, N., Okuto, E., & Waititu, H. (2019). Application of Cox PH model on broilers in La Nyevu poultry farm in Kaloleni sub-county; A survival analysis case study. Bulletin of Mathematics and Statistics Research.

Waititu, H. W., & Njenga, E. (2016). Non-parametric variance estimation using donor imputation method. American Journal of Theoretical and Applied Statistics. https://doi.org/10.11648/j.ajtas.20160505.11