by Usha Govindarajulu | Sep 25, 2024 | Biostatistics, Blog, Usha Govindarajulu
September 25, 2024 This article focused how changing living arrangements was associated with suicide risk using survival analysis along with causal inference. The authors admitted that traditional methods like Cox model analysis were not sufficient to handle...
by Usha Govindarajulu | Aug 15, 2024 | Blog
August 15, 2024 In clinical trials that use time to event endpoints, a traditional measure has been using the hazard ratio derived from a Cox proportional hazard regression, but one must satisfy this assumption. Over time, measures that have relaxed this assumption...
by Usha Govindarajulu | Jan 17, 2024 | Biostatistics, Blog, Usha Govindarajulu
January 17, 2023 In an article that appeared in Biometrical Journal, Hoogland et al (2023) had aimed to combine the benefits of flexible parametric survival modeling and regularization in order to improve risk prediction modeling in the context of time-to-event data....
by Usha Govindarajulu | Jan 3, 2024 | Biostatistics, Blog, Usha Govindarajulu
January 3, 2023 In an article that appeared in Biometrical Journal, Le Bourdonnec et al (2023) discussed a method to address unmeasured confounding in cohort studies by an instrumental varible (IV) method for a time fixed expousre on an outcome trajectory, repeatedly...
by Usha Govindarajulu | Dec 6, 2023 | Biostatistics, Blog, Usha Govindarajulu
December 6, 2023 In article that appeared in Biostatistics, Wu et al describe a joint modeling approach of longitduinal data like quality of life and survival data on a retrospective time scale and handling of informative censoring issues in a two arm clinical trial...