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 | 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 | 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...
by Usha Govindarajulu | Oct 31, 2018 | Biostatistics, Blog, Usha Govindarajulu
Abstract To allow for non-linear exposure-response relationships, we applied flexible non-parametric smoothing techniques to models of time to lung cancer mortality in two occupational cohorts with skewed exposure distributions. We focused on three different...
