Regressionsanalysen sind von Konfundierungseffekten betroffen, wenn Drittvariablen gleichzeitig mit Zielgrößen und Kovariablen korreliert sind. Klassische Regressionsmodelle sind in diesen Fällen nicht in der Lage, Kovariablen- und Drittvariableneffekte voneinander zu unterscheiden. Die...

The Cox proportional hazards model is the most commonly used method when analyzing the impact of covariates on continuous survival times. In its classical form, the Cox model was introduced in the setting of right-censored observations. However, in practice other sampling schemes are frequently...

The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as linearity of the predictor or the...

There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC) simulation techniques which allow the...

4208 In many practical situations, simple regression models suffer from the fact that the dependence of responses on covariates can not be sufficiently described by a purely parametric predictor. For example effects of continuous covariates may be nonlinear or complex interactions between...