Dr. Onyango, Nelson Owuor

Dr. Nelson O. Onyango has a PhD in Biostatistics from the Technical University of Munich, Germany, a Master of Science degree (Biostatistics) and Bachelor’s degree in Education from the University of Nairobi. He has over 14 years teaching experience in biostatistics at the University of Nairobi, Kenya. Besides, he conducts research and manages research grant projects.



Nuwasiima, A, et al.  2017.  Predictors of HIV prevention knowledge and sexual behaviors among students at Makerere University Kampala, Uganda. al Epidemiology, Biostatistics and Public Health. 14(4)


Otieno, S, et al.  2015.  The role of agri-business incentive on under-five child immunization in Trans-Nzoia County. East African Journal of Public Health. 12(12):1054-1059.
Orowe, I, Weke P.  2015.  Multistate Modelling Vertical Transmission and Determination of R0 Using Transition Intensities.. HIKARI Applied Mathematical Sciences. 9(79):3941–3956.


Onyango Nelson O., MJ.  2014.  Determination of optimal vaccination strategies using an orbital stability threshold from periodically driven systems. Journal of Mathematical Biology. 68(3):763--784.
Onyango N.O., Mueller J., MSK.  2014.  Optimal Vaccination Strategies in an SIR epidemic model with time scales. , Rennes, France


N.O., O.  2010.  Theory and Practice of Mixed Modeling. , Saarbrucken: VDM-Verlag Dr.Mueller
NO, O.  2010.  Optimal Vaccination Strategies in periodic settings and Threshold conditions: A Survey.. . International Journal of Biomathematics and Biostatistics . 1(2):193-201.


Onyango, NO.  2009.  On the Linear Mixed Effects Regression (lmer) R Function for Nested Animal Breeding Data. AbstractOn the Linear Mixed Effects Regression (lmer) R Function for Nested Animal Breeding Data

This work highlights aspects of the R lmer function for a case where the dataset is nested, highly unbalanced, involves mixed effects and repeated measurements. The lmer function is part of the lme4 package of the statistical software R. The dataset used in the study is simulated from a survey of cow milk off takes from a group of Herds in Uganda, Africa. The purpose of the survey was to identify quality breeds of African Indigenous cattle for purposes of genetic breeding following the difficulties involved in implantation of foreign breeds of cattle in Africa. The work highlights the use of mixed model analysis in the context of animal breed selection. The exposition is accessible to readers with an intermediate background in statistics. Some previous exposure to R is helpful as well as some familiarity with mixed models.

NO, O.  2009.  On the lmer function for nested animal breeding data. CSBIGS. 4(1):44-58.


Onyango N. O., Achia T., RJ.  2007.  Case Study 2: Identification of Elite Ankole Cattle in a Herd Monitoring Study in Uganda.. Biometrics and Research Methods Teaching Resource Version 1. , Nairobi: ILRI

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