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 | Jul 31, 2024 | Biostatistics, Blog, Usha Govindarajulu
July 31, 2024 The authors discussed applications of artificial intelligence (AI)/machine learning algorithms in survival analysis to skin cancer research publications. They reported on 16 such publications. Supervised machine learning (ML) would have used existing...
by Usha Govindarajulu | Jul 17, 2024 | Biostatistics, Blog, Usha Govindarajulu
July 17, 2024 The authors have written a new article about using average hazard (AH) as compared to restricted mean survival time (RMST) as a measure instead of hazard ratios which are instantaneous measures of effect generally obtained through estimation of a Cox...
by Usha Govindarajulu | Jul 3, 2024 | Biostatistics, Blog, Usha Govindarajulu
July 4, 2024 The authors discussed the use of the standardized mortality ratio (SMR) to compare survival across centers, especially in the context of U.S. kidney transplant center evaluation. The SMR is calculated based on indirect standardization methods in general...
by Usha Govindarajulu | Jun 20, 2024 | Blog, Usha Govindarajulu
The goals of this paper were to provide a set of conditions for inverse probability weights (IPW) to target a subpopulation of the patients who have clinical equipose, establish a relationship between matching weights and overlap weight estimators, and use the beta...
by Usha Govindarajulu | Jun 5, 2024 | Biostatistics, Blog, Usha Govindarajulu
June 5, 2024 The authors have come up with a proportional risk model to assess treatment effect in time-to-event data. One thing they first discussed which is important to note is that relative risk (RR) and hazard ratio (HR) are definitely not the same...
