by Usha Govindarajulu | Aug 16, 2023 | Biostatistics, Blog, COVID-19, Epidemiology, Healtcare, Usha Govindarajulu
The authors developed a proportional incidence model to estimate vaccine effectiveness (VE) but at the population level. Understanding VE during the COVID-19 pandemic was very important. Since obtaining individual level data linkages, the authors used aggregated...
by Usha Govindarajulu | Aug 2, 2023 | Biostatistics, Blog, Usha Govindarajulu
August 2, 2023 In this article published in June online, Lancker et al describe a way for valid inference of hazard ratios from a Cox regression after variable selection. The problem has been that it is unknown which amount of covariates to use to control for...
by Usha Govindarajulu | Jul 19, 2023 | Biostatistics, Usha Govindarajulu
Statistical issues in survival analysis (Part XI) July 19, 2023 The authors, Ning et al, have proposed what they refer to as a “broad class” of “so called” Cox-Aalen transformation models which have elements of both multiplicative and additive covariate effects...
by Usha Govindarajulu | Jul 6, 2023 | Biostatistics, Blog, Usha Govindarajulu
July 5, 2023 The restricted mean survival time (RMST) is a concept that has been invented in survival analysis as an alternative to the hazards ratio, which can be difficult to interpret and also, as derived from Cox model, can have difficulty fitting into the...
by Usha Govindarajulu | Jun 23, 2023 | Blog, Usha Govindarajulu
June 21, 2023 Quantile regression has been around for awhile but has not been used so extensivly in survival analysis, namely for comparisons at the population level. The authors, Williamson et al, proposed analyzing relative survival data using quantile regression...
