by Usha Govindarajulu | Nov 24, 2023 | Biostatistics, Blog, Usha Govindarajulu
Statistical issues in survival analysis (Part XVIII) November 22, 2023 In this article that appeared in Journal of Probability and Statistics, the authors described a new test as an alternative to the log-rank test to compare late differences between survival curves. ...
by Usha Govindarajulu | Oct 25, 2023 | Biostatistics, Blog, Usha Govindarajulu
October 15, 2023 The authors discussed how to handle model joint survival and longitudinal modeling in the presence of informative censoring caused by informative dropouts by participants in a study. The authors framed this in terms of palliative care studies where...
by Usha Govindarajulu | Oct 11, 2023 | Biostatistics, Blog, Usha Govindarajulu
October 11, 2023 In this recent article by Hoogland et al, the authors have proposed combining flexible parametric survival modeling with regularization in order to improve risk prediction modeling for time-to-event data and, thus, they made a unified regularation...
by Usha Govindarajulu | Sep 27, 2023 | Biostatistics, Blog, Usha Govindarajulu
September 25, 2023 The authors, Hanke et al, discussed variable selction methods for linear regression and that the best subset selection (BSS) is not always the best choice. After Bertsimas et al (2016) pushed BSS as a mixed-integer optimization problem (MIO) so...
by Usha Govindarajulu | Sep 14, 2023 | Biostatistics, Usha Govindarajulu
September 13, 2023 In their paper, the authors, Wang et al focused on estimation of casual effects of a treatment on survival outcomes with censoring with propensity score (PS) adjustment. They also used alternative measures of survival like restricted average causal...
by Usha Govindarajulu | Aug 30, 2023 | Biostatistics, Blog, Usha Govindarajulu
August 30, 2023 In this article that appeared in a special issue in the Biometrical Journal, Chen et al describe how restricted mean survival time (RMST), an alternative representation of survival time, can be adapted to have clustering. They were motivated by...
