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Dr. Tsirizani Mwalimu Mumderanji Kaombe

SENIOR LECTURER
Mathematical Sciences

Research Areas

Regression Diagnostics, Multivariate linear and non-linear models, Time-to-event data analysis, Bivariate (Joint) Distribution Models, and general Biostatistics,

Profile

Tsirizani Kaombe is a practicing statistician serving as a lecturer, researcher, and consultant in the Department of Mathematical Sciences at the University of Malawi. Over the past five years, he has successfully supervised seven master's theses in biostatistics and is currently supervising four more. During the same time, he has externally examined Ph.D. and Master's theses in statistics for the Universities of Cape Town and KwaZulu Natal in South Africa, and the Malawi University of Science and Technology. He is a journal reviewer for Archives of Public Health, Journal of Big Data, BMC Research Notes, BMC Medical Research Methodology, BMJ Open, BMC Public Health, BMC Pediatrics, Communications Medicine, Scientific Reports, and BMC Infectious Diseases. He has worked as a consultant, evaluating health, education, and social sciences projects. He has additional expertise in designing strategic plans for organisations.

Publications

  • Journal Article
    Kaombe, T.M. Analysis of outlier villages with high under-five mortality rates in Malawi using mixed-effects logistic regression model residuals. BMC Public Health 25, 2221 (2025). https://doi.org/10.1186/s12889-025-23510-9 (2025)
    https://doi.org/10.1186/s12889-025-23510-9
  • 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
    Hamuza, G.A., Singogo, E. & Kaombe, T.M. Application of multivariate binary logistic regression grouped outlier statistics and geospatial logistic model to identify villages having unusual health-seeking habits for childhood malaria in Malawi. Malar J 23, 246 (2024). https://doi.org/10.1186/s12936-024-05070-2 (2024)
    https://doi.org/10.1186/s12936-024-05070-2
  • Journal Article
    Mponda, E., Kaombe, T. Comparison of univariate and bivariate Poisson regression methods in the analysis of determinants of female schooling and fertility in Malawi. BMC Public Health 24, 2285 (2024). https://doi.org/10.1186/s12889-024-19816-9 (2024)
    https://doi.org/10.1186/s12889-024-19816-9
  • Book Chapters
    Kaombe, T.M., Hamuza, G.A. (2024). Survey Design Effect in the Prediction of Events for Categorical Health Outcomes Through Regression Methods: Evidence from Malawi Under-Five Mortality Survey Data: 2000–2016. In: Chen, DG., Coelho, C.A. (eds) Biostatistics Modeling and Public Health Applications. Emerging Topics in Statistics and Biostatistics . Springer, Cham. https://doi.org/10.1007/978-3-031-69690-9_11 (2024)
    https://doi.org/10.1007/978-3-031-69690-9_11
  • 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