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 | Jan 31, 2024 | Biostatistics, Blog, COVID-19, Usha Govindarajulu
January 31, 2024 In an article that appeared in Biometrical Journal, Hu described a new random-intercept accelerated failure time model with Bayesian additive regression trees (riAFT-BART), which can be used to draw causal inferences on population treatment effectts...
by Usha Govindarajulu | Dec 20, 2023 | Biostatistics, Usha Govindarajulu
December 20, 2023 In article that appeared in Statistics in Medicine, Denz et al explored different methods for modeling of adjusted survival curves especially in observational studies, which tend to have issues with confounding. The authors also brought in...
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...
by Usha Govindarajulu | Aug 30, 2023 | Biostatistics, Blog, Usha Govindarajulu
August 30, 2023 In this article that appeared in a special issue in the Biometrical Journal, Chen et al describe how restricted mean survival time (RMST), an alternative representation of survival time, can be adapted to have clustering. They were motivated by...
