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...

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...

In this article we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variable are modelles through a flexible semiparametric predictor. We extend existing LVM with simple linear covariate effects by including...

Extensions of the traditional Cox proportional hazard model, concerning the following features are often desirable in applications: Simultaneous nonparametric estimation of baseline hazard and usual fixed covariate effects, modelling and detection of time-varying covariate effects and nonlinear...