by Usha Govindarajulu | Jul 1, 2026 | Biostatistics, Blog, Usha Govindarajulu
July 1, 2026 The authors were motivated by comparing future antibiotic resistance levels from different treatments but found some challenges as patients may only survive under one of the treatments. They approached this through a time-to-event analysis and...
by Usha Govindarajulu | May 6, 2026 | Biostatistics, Blog, Usha Govindarajulu
May 6, 2026 The win ratio introduced by Pocock et al (2012) has become a popular measure to summarize composite endpoints in clinical trials. It essentially prioritizes important events over lesser ones using an effect size as the relative frequency of wins (more...
by Usha Govindarajulu | Apr 22, 2026 | Biostatistics, Blog, Machine Learning, Usha Govindarajulu
April 22, 2026 Written by, In this article, they studied regression analysis of arbitrarily censored and left-truncated data under a popular semiparametric proportional odds model. They developed a new estimation approach via an expectation and maximization algorithm...
by Usha Govindarajulu | Apr 8, 2026 | Biostatistics, Blog, Usha Govindarajulu
April 8, 2026 The Restricted Mean Survival Time (RMST) is a metric to compare survival between two treatment groups without relying on proportional hazards, especially that hazard ratios are constant over time. For covariate adjustment, Andersen et al’s (2004) method...
by Usha Govindarajulu | Mar 25, 2026 | Biostatistics, Blog, Usha Govindarajulu
March 25, 2026 The goal of this article was to present a methodology to design and analyze an adaptive clinical trial with sample size recalculation at interim analysis, when the restricted mean survival time (RMST) is the primary endpoint. Especially, we focus on the...
