… ) or a Cox model (Cox, 1972). We show that there is an advantage to using conditional
additive hazard models for the data simulation, because this results in an additive form for the …

… based on the additive hazards model. The emphasis is on a … the additive hazards model and
a sequential linear model for … survival as well as cumulative hazards. Our results generalize …

… For massive survival data, we propose a subsampling algorithm to efficiently approximate
the estimates of regression parameters in the additive hazards model. We establish …

… model their impact on the frequency and severity of the events, we apply generalized additive
models … The advantage of a GAMLSS approach is that the models can utilize all available …

… the additive hazards model, where we define the treatment effect as a difference in the hazards
… We then develop several refinements and extensions, including a new hazard difference (…

… We develop a novel semiparametric hazards regression model by modeling the hazard
function as a product of a parametric baseline hazard function and a nonparametric component …

… to satisfy the basic assumptions wherein additive hazard model is a good alternative. Unlike
… introduce the additive hazard quantile model. In Sect. 4, some properties of the model are …

… specific hazard functions … hazards regression model leading to direct inference on the
cumulative incidence function. Others have proposed regression methods that more directly model …

… exponential additive mixed model (PAMM) is a model class … with enough flexibility for modeling
complex hazard structures. We … Therefore, we model the hazard for arrival at time t given …

… the general framework of flexible hazard-based regression models and describe their
extension to excess hazard and mixed-effect (possibly, excess) hazard models. We then proceed …