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...
by Usha Govindarajulu | Mar 29, 2023 | Biostatistics, Blog, New York
Statistical issues in general (Part I) March 27, 2023 In an article that first appeared in 2021 in Biometrics but is now finally open access in the same journal , the authors, Moss and Bin discuss how publication bias and p-hacking have had strong effects on...
by Usha Govindarajulu | Mar 16, 2023 | Biostatistics, Blog, COVID-19, Healtcare, Machine Learning, Usha Govindarajulu
March 15, 2023 In a recent article that appeared in Science News, a teach from Johns Hopkins University discussed their proof of concept study to show how their machine learning system used electronic health data to make predictions to determine who would be most...
