activity
20152020
most citedNon Proportional Odds Models are Widely Dispensable -- Sparser Modeling based on Parametric and Additive Location-Shift Approaches

2 citations · 3 across the 5 of their papers we have counts for

collaborators
Showing stat.MEShow all

8 papers · 1 filter

stat.ME20202 cited

Non Proportional Odds Models are Widely Dispensable -- Sparser Modeling based on Parametric and Additive Location-Shift Approaches

Gerhard Tutz, Moritz Berger

The potential of location-shift models to find adequate models between the proportional odds model and the non-proportional odds model is investigated. It is demonstrated that thes…

stat.ME2020

Transition Models for Count Data: a Flexible Alternative to Fixed Distribution Models

Moritz Berger, Gerhard Tutz

A flexible semiparametric class of models is introduced that offers an alternative to classical regression models for count data as the Poisson and negative binomial model, as well…

stat.ME2020

Assessing the Calibration of Subdistribution Hazard Models in Discrete Time

Moritz Berger, Matthias Schmid

The generalization performance of a risk prediction model can be evaluated by its calibration, which measures the agreement between predicted and observed outcomes on external vali…

stat.ME2019

Tree-Structured Scale Effects in Binary and Ordinal Regression

Gerhard Tutz, Moritz Berger

In binary and ordinal regression one can distinguish between a location component and a scaling component. While the former determines the location within the range of the response…

stat.ME20191 cited

A Random Forest Approach for Modeling Bounded Outcomes

Leonie Weinhold, Matthias Schmid, Marvin N. Wright +1

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of complex predictor-response relat…

stat.ME2017

Tree-Structured Modelling of Varying Coefficients

Moritz Berger, Gerhard Tutz, Matthias Schmid

The varying-coefficient model is a strong tool for the modelling of interactions in generalized regression. It is easy to apply if both the variables that are modified as well as t…