pammtools: Piece-wise exponential Additive Mixed Modeling tools

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Authors Andreas Bender, Fabian Scheipl
Journal/Conference Name arXiv:1806.01042 [stat]
Paper Category
Paper Abstract 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.
Date of publication 2018
Code Programming Language R
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