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stat.ME2026
Detecting Early and Late Divergences in Survival Curves Using Nonparametric Effect Measures
Patrick B. Langthaler, Jun Ma, Jonas Beck
Clinical trials often show treatment curves that diverge early and converge later, or vice versa patterns that are poorly captured by the proportional-hazards assumption. We develo…
stat.ME2024
A maximum penalised likelihood approach for semiparametric accelerated failure time models with time-varying covariates and partly interval censoring
Aishwarya Bhaskaran, Ding Ma, Benoit Liquet +4
Accelerated failure time (AFT) models are frequently used to model survival data, providing a direct quantification of the relationship between event times and covariates. These mo…
stat.ME2024★ 2 cited
Mixture cure semiparametric additive hazard models under partly interval censoring -- a penalized likelihood approach
Jinqing Li, Jun Ma
Survival analysis can sometimes involve individuals who will not experience the event of interest, forming what is known as the cured group. Identifying such individuals is not alw…