Research Areas

Diagnostic statistics, Multivariate linear and non-linear models, Time-to-event data analysis, and general Biostatistics,

Profile

Dr. Tsirizani Kaombe is a practicing statistician serving as lecturer, consultant, and researcher in the Department of Mathematical Sciences at University of Malawi. His recent publications are available at https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Tsirizani+M.+Kaombe&btnG=. He holds a Ph.D. degree in Biostatistics obtained from the University of Malawi-Chancellor College in the year 2020. His Ph.D. thesis was titled "Identifying outlying and influential clusters in the analysis of multivariate survival data" and it was supervised by Prof. Samuel Manda of University of Pretoria. Dr. Kaombe is an awardee of 2018 Best Ph.D. Oral Presentation at the Sub-Saharan Africa Biostatistics Consortium (SSACAB) Conference and AGM, held on 10-14 Sept 2018, at University of Nairobi, Kenya. Overall, his research interests are in Diagnostic statistics; Multivariate linear and non-linear models; Time-to-event data analysis; and their application. He is, since 2021, a reviewer to BMC Public Health, BMJ Open, and PeerJ journals. He is a member of International Biometric Society (IBS), Southern Africa Mathematical Sciences Association (SAMSA), and Statistical Association of Malawi. Over the years, he has taught undergraduate courses such as: Distribution theory; Statistical Quality Control; Introduction to Probability and Statistics; Hypothesis testing; Introduction to Generalized Linear Models; Linear regression models; Experimental designs and analysis; Advanced Calculus; Linear Algebra; and Ordinary Differential Equations, and postgraduate course of Statistical computing with STATA. He has successfully supervised 3 MSc theses in Biostatistics since 2016 and over 30 undergraduate statistics projects. He has externally examined one Ph.D. thesis in Statistics and one MSc. thesis in statistics, both from University of Cape Town. He has worked as consultant in evaluating projects in health, education, and social sciences. He has also expertise in designing strategic plans and monitoring and evaluation systems for organisations and projects. On community engagement activities, he currently serves as Chairperson of the Board of Directors for Centre for Democracy and Elections (CEDE), a registered Civil Society Organization (CSO) in Malawi focusing on democracy advocacy and monitoring.

Publications

• Journal Article
  Kaombe, T. M. (2024). A bivariate Poisson regression to analyse impact of outlier women on correlation between female schooling and fertility in Malawi. BMC Women's Health, 24(1), 1-18. (2024)
  https://bmcwomenshealth.biomedcentral.com/articles/10.1186/s12905-024-02891-w

  ---

• Journal Article
  Kaombe, T. M., Banda, J. C., Hamuza, G. A., and Muula, A. S. (2023). Bivariate logistic regression model diagnostics applied to analysis of outlier cancer patients with comorbid diabetes and hypertension in malawi. Scientific Reports, 13(1):8340. (2023)
  https://www.nature.com/articles/s41598-023-35475-z

  ---

• Journal Article
  Kaombe, T. M. and Hamuza, G. A. (2023). Impact of ignoring sampling design in the prediction of binary health outcomes through logistic regression: evidence from malawi demographic and health survey under-five mortality data; 2000-2016. BMC Public Health, 23(1):1–12. (2023)
  https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-023-16544-4

  ---

• Journal Article
  Tsirizani M. Kaombe and Samuel O.M. Manda (2022): A Novel Outlier Statistic in Multivariate Survival Models and its Application to Identify Unusual Under-Five Mortality Sub-Districts in Malawi, Journal of Applied Statistics, DOI: 10.1080/02664763.2022.2043255 (2022)
  https://www.tandfonline.com/doi/full/10.1080/02664763.2022.2043255

  ---

• Journal Article
  Natasha Sakala and Tsirizani M. Kaombe (2022). Analysing outlier communities to child birth weight outcomes in Malawi: application of multinomial logistic regression model diagnostics. BMC Pediatrics, 22:682, https://doi.org/10.1186/s12887-022-03742-z (2022)
  https://bmcpediatr.biomedcentral.com/articles/10.1186/s12887-022-03742-z

  ---

• Book Chapters
  Tsirizani M. Kaombe and Samuel O.M. Manda (2022). Identifying outlying and influential clusters in multivariate survival data models. In: Chen, DG., Manda, S.O.M., Chirwa, T.F. (eds) Modern Biostatistical Methods for Evidence-Based Global Health Research. Emerging Topics in Statistics and Biostatistics. Springer, Cham. https://doi.org/10.1007/978-3-031-11012-2_15 (2022)
  https://link.springer.com/chapter/10.1007/978-3-031-11012-2_15

  ---

• Journal Article
  Tsirizani M. Kaombe & Samuel O.M. Manda (2021): Detecting influential data in multivariate survival models, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1982983 (2021)
  https://www.tandfonline.com/doi/full/10.1080/03610926.2021.1982983

  ---