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 | Feb 14, 2024 | Blog
In an article in Biometrical Journal, Heinze et al discussed phases of methodological research in biostatistics. The authors of this publication are all members of an international STRATOS (STRengthening Analytical Thinking for Observational Studies) Intiative, whose...
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 | 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...
