by Usha Govindarajulu | Jul 2, 2025 | Biostatistics, Blog, Usha Govindarajulu
July 2, 2025 The importance of evaluating a longitudinal biomarker in survival analysis for overall or disease-free survival can be important. The authors have defined a new joint model for a longitudinal biomarker and a time-to-event endpoint, taking into account...
by Usha Govindarajulu | Apr 23, 2025 | Biostatistics, Blog, Usha Govindarajulu
April 23, 2025 The authors have discussed a sample size calculation for restricted mean survival time (RMST) in augmented tests. The RMST was developed as an alternative measure of survival that is non-parametric and does not reply on parametric constraints. It had...
by Usha Govindarajulu | Apr 9, 2025 | Biostatistics, Blog, Usha Govindarajulu
April 9, 2025 The authors have generalized the pseudo-observations approach to bivariate survival data subject to right censoring. Pseudo-observations approach was originally developed by Anderson (2003) for estimating covariates effect on time-to-event data. This...
by Usha Govindarajulu | Mar 27, 2025 | Biostatistics, Blog, Usha Govindarajulu
March 26, 2025 Their primary goal of their paper was to introduce a novel frailty model based on the weighted Lindley (WL) distribution for modeling clustered survival data. They used the weighted Lindley as the frailty distribution. This was a two parameter...
by Usha Govindarajulu | Mar 12, 2025 | Biostatistics, Blog, Healtcare
March 12, 2025 The authors used a novel method based on wavelet filtering and landmarking to obtain the prognostic role of a biomarker in patient death. Wavelet filters have been common in time series data to extract features and reduce noise. They also utilized...
