tramME: Mixed-Effects Transformation Models Using Template Model Builder

Abstract

Linear transformation models constitute a general family of parametric regression models for discrete and continuous responses. To accommodate correlated responses, the model is extended by incorporating mixed effects. This article presents the R package tramME , which builds on existing implementations of transformation models ( mlt and tram packages) as well as Laplace approximation and automatic differentiation (using the TMB package), to calculate estimates and perform likelihood inference in mixed-effects transformation models. The resulting framework can be readily applied to a wide range of regression problems with grouped data structures.