Dr Eliud Kibuchi
- Research Associate (MRC/CSO Social & Public Health Sciences Unit)
I'm a Research Associate at the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow.
I hold a BSc in Applied Statistics with Information Technology from Maseno University, Kenya, an MSc in Environmental Statistics from the University of Glasgow, UK, and a PhD in Social Statistics from University of Southampton, UK. The title of my PhD thesis is “An Investigation of Methods for Improving Survey Data Quality” and involved application of Bayesian methods, multilevel modelling and propensity score matching approaches to investigate nonresponse, interviewer effects, incentives effects and mode-effects in surveys.
During my PhD, I secured a 3-month fellowship visit at the Wellcome Trust, London where I investigated the quality of Global Monitor Survey 2018, the world’s largest study into how people around the world think and feel about science and major health challenges. The statistical approaches I applied included exploratory factor analysis, principal component analysis, multi-group confirmatory factor analysis and multilevel modelling.
I have also previously worked as a Research Officer (medical statistics) at Kenya Medical Research Institute (KEMRI) -Wellcome Trust, Nairobi, Kenya where I applied Bayesian spatial-temporal models and small area estimation using integrated nested Laplace approximations (INLA) to predict malaria risks in Africa and Arabian Peninsula. I have also worked as a Data Analyst at Kenya Forest Service (KFS) in Nairobi, Kenya.
I am currently involved in three projects: 1) Enhancing the value of Understanding Society by harnessing record-linkage to address bias associated with nonparticipation, 2) Improving survey-based alcohol consumption estimates for assessing the impact of minimum unit pricing (MUP) in Scotland and 3) Accountability and Responsiveness in Informal Settlements for Equity in Health and Wellbeing (ARISE) in Bangladesh, India, Kenya and Sierra Leone.
My research interests involve application of statistical approaches to address nonparticipation bias, missing data, health inequalities and global health issues.
I contribute to the Master of Public Health by teaching measurement and bias in survey data.