by Usha Govindarajulu | Jan 14, 2026 | Biostatistics, Blog, Usha Govindarajulu
January 14, 2026 To evaluate the performance of a prediction model in time-to-event outcomes with censoring is very difficult. Interval censoring and competing risks present additional challenges. They proposed two methods to deal with interval censoring: a...
by Usha Govindarajulu | Dec 4, 2025 | Biostatistics, Blog, Usha Govindarajulu
December 3, 2025 In this short article, Per Kragh Andersen has given a rebuttal to the article by Beyersmann et al (2025) which was about hazards constituting key quantities for time-to-event data. Despite arguments by other statisticians, Beyersmann et al. (2025)...
by Usha Govindarajulu | Sep 11, 2024 | Biostatistics, Blog, Usha Govindarajulu
September 11, 2024 This article focused on joint modeling in the presence of informative censoring in a retrospective analysis in palliative care research. There has been a lack of statistical models to handle longitudinal quality of life (QOL) data and...
by Usha Govindarajulu | Aug 28, 2024 | Biostatistics
August 28, 2024 The authors have proposed using imputed data from subdistribution weights to train on machine learning methods for competing risk data. The authors focused on the random survival forest (RSF) method which it stars with a number of bootstrap samples...
by Usha Govindarajulu | Mar 27, 2024 | Biostatistics, Blog, Usha Govindarajulu
March 27, 2024 In this article, the authors described their Schemper-Henderson measure to account for explained variation for survival outcomes, extended to allow for competing risks. They defied explained variation as the relative gain in predictive accuracy when...
