Background With progress on both the theoretical and the computational fronts the use of
spline modelling has become an established tool in statistical regression analysis. An …

Distributional regression models that overcome the traditional focus on relating the
conditional mean of the response to explanatory variables and instead target either the …

Count data can be analyzed using generalized linear mixed models when observations are
correlated in ways that require random effects. However, count data are often zero-inflated …

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …

This is a book about statistical distributions, their properties, and their application to
modelling the dependence of the location, scale, and shape of the distribution of a response …

Background Although CT-based body composition (BC) metrics may inform disease risk and
outcomes, obtaining these metrics has been too resource intensive for large-scale use …

Language is universal, but it has few indisputably universal characteristics, with cross-
linguistic variation being the norm. For example, languages differ greatly in the number of …

GAMLSS is a general framework for fitting regression type models where the distribution of
the response variable does not have to belong to the exponential family and includes highly …

Background Historically social connection has been an important way through which
humans have coped with large-scale threatening events. In the context of the COVID-19 …

Alle im vorigen Kapitel beschriebenen Problemstellungen besitzen eine wesentliche
Gemeinsamkeit: Eigenschaften einer Zielvariablen y sollen in Abhängigkeit von Kovariablen …