… A key issue in this book is extensions of the Cox model and alternative models with most
of them having the specific aim to be able to deal with time-varying effects of covariates in …

… In Sections 2 and 3, we present the non-parametric additive regression model and the
semiparametric additive regression model for the excess hazard, respectively. To avoid confusion …

… In most existing methods for varying coefficient models, … a dynamic Cox regression model
for interval censored data in a … points are covariate specific and estimated from the data. The …

… published on the topic of survival analysis. This book is … model as the benchmark model for
survival data. Here additive hazards model are introduced to the reader before the Cox model …

… for the survival and reliability data analysis. These dynamic regression models that we
have … proportional hazards and accelerated failure time models contain the possibly time-…

… projection techniques, dynamic modeling [23] … regression analysis, as Cox models do not
rely on any specific assumption on the parametric shape of the hazard function. In this analysis, …

… dynamic process provides challenges in formulating a model that are not present in settings
where a typical linear or logistic regression model … link and then the section on survival data, …

… Such prediction models must be updated in order to remain useful. In this study, we investigate
dynamic model updating of clinical survival prediction models. In contrast to discrete or …

… Then, y i is the minimum of the censoring time C i and the survival time T i . To build a
regression model, we introduce covariates through θ i and write θ i ≡ θ(x i ′β) = exp(x i ′β), …

… facilitates the implementation of survival models for credit risk data. In particular, if we … obtain
the standard logistic regression model. Risk factors used in credit risk models fall into three …