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...
by Usha Govindarajulu | Feb 28, 2024 | Blog
February 26, 2024 TABLE 1. Summary of the available methods for survival regression with competing risks (CR). Model Type Proportional hazards (PH) High dimensions (�) Missing data Approaches based on a cause-specific hazard specification Cox proportional CS hazard...
by Usha Govindarajulu | Nov 11, 2023 | Biostatistics, Blog
November 9, 2023 In this article that appeared in a special issue in the Biometrical Journal, Morelle et al described a joint modeling approach to account for the longitudinal followup of patients at subsequent hospitalization or competing risk. While most prognostic...
