by Usha Govindarajulu | Jun 9, 2023 | Biostatistics, Blog, Machine Learning, Usha Govindarajulu
June 7, 2023 The authors reviewed methods for complex survival data in terms of frailty models, like the recent advances and R packages. They explored areas of clustered outcomes, competing risks, illness-death model. They did admit their review did not cover two...
by Usha Govindarajulu | May 24, 2023 | Biostatistics, Blog, Professor, Usha Govindarajulu
May 24, 2023 The authors developed a semiparametric maximum likelihood estimation procedure via a kernel smoothed-aided expectation-maximization algorithm. The variances for this were estimated through weighted bootstrap. The authors focused on this for the...
by Usha Govindarajulu | May 10, 2023 | Biostatistics, Blog, Usha Govindarajulu
May 10, 2023 The authors Sun et al present a semi-competing risks framework using a flexible two-parameter copula-based semiparametric transformation model with interval censoring and left truncation. The semi-parametric transformation model allow both proportional...
by Usha Govindarajulu | Apr 26, 2023 | Biostatistics, Blog, COVID-19, Epidemiology, Healtcare, Usha Govindarajulu
April 26, 2023 In a recent article that appeared in Statistics in Medicine, Arntzen et al discussed that quarantine time length for persons infected with SARS-CoV-2 was based on incubation time distribution estimates. However, given the unknowns about time to...
by Usha Govindarajulu | Apr 12, 2023 | Biostatistics, Blog, Usha Govindarajulu
April 12, 2023 The authors, Ozaki and Ninomiya have presented how information criteria, like AIC, can be adapted when detecting change points in a Cox proportional hazards regression. The authors motivated the use of change-points due to onset of efficacy being...
