Kaombe, Tsirizani M.Manda, S.O.M. (Samuel)2022-07-082023Tsirizani M. Kaombe & Samuel O. M. Manda (2023) A novel outlier statistic in multivariate survival models and its application to identify unusual underfive mortality sub-districts in Malawi, Journal of Applied Statistics, 50:8, 1836-1852, DOI: 10.1080/02664763.2022.2043255.0266-4763 (print)1360-0532 (online)10.1080/02664763.2022.2043255https://repository.up.ac.za/handle/2263/86077Although under-five mortality (U5M) rates have declined worldwide, many countries in sub-Saharan Africa still have much higher rates. Detection of subnational areas with unusually higher U5M rates could support targeted high impact child health interventions. We propose a novel group outlier detection statistic for identifying areas with extreme U5M rates under a multivariate survival data model. The performance of the proposed statistic was evaluated through a simulation study. We applied the proposed method to an analysis of child survival data in Malawi to identify sub-districts with unusually higher or lower U5M rates. The simulation study showed that the proposed outlier statistic can detect unusual high or low mortality groups with a high accuracy of at least 90%, for datasets with at least 50 clusters of size 80 or more. In the application, at most 7 U5M outlier sub-districts were identified, based on the best fitting model as measured by the Akaike information criterion (AIC).en© 2021 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in Journal of Applied Statistics, vol. 50, no. 8, pp. 1836-1852, 2023. doi : .10.1080/02664763.2022.2043255. Journal of Applied Statistics is available online at : http://www.tandfonline.comloi/cjas20.Clustered dataMultivariate Cox PH modelOutlier statisticUnder-five mortality (U5M)Outlying sub-districtsPostprint Article