  This article introduces the pammtools package, which facilitates data
transformation, estimation and interpretation of Piece-wise exponential
Additive Mixed Models. A special focus is on time-varying effects and
cumulative effects of time-dependent covariates, where multiple past
observations of a covariate can cumulatively affect the hazard, possibly
weighted by a non-linear function. The package provides functions for
convenient simulation and visualization of such effects as well as a robust and
versatile function to transform time-to-event data from standard formats to a
format suitable for their estimation. The models can be represented as
Generalized Additive Mixed Models and estimated using the R package mgcv. Many
examples on real and simulated data as well as the respective R code are
provided throughout the article.
