pammtools - Piece-Wise Exponential Additive Mixed Modeling Tools for Survival Analysis
The Piece-wise exponential (Additive Mixed) Model (PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a powerful model class for the analysis of survival (or time-to-event) data, based on Generalized Additive (Mixed) Models (GA(M)Ms). It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, random effects, time-varying effects, time-dependent covariates and cumulative effects (Bender and others (2019)), as well as support for left-truncated data as well as competing risks, recurrent events and multi-state settings. pammtools provides tidy workflow for survival analysis with PAMMs, including data simulation, transformation and other functions for data preprocessing and model post-processing as well as visualization.
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additive-modelspammpammtoolspiece-wise-exponentialsurvival-analysis
10.40 score 51 stars 9 dependents 432 scripts 3.9k downloads
coalitions - Bayesian "Now-Cast" Estimation of Event Probabilities in Multi-Party Democracies
An implementation of a Bayesian framework for the opinion poll based estimation of event probabilities in multi-party electoral systems (Bender and Bauer (2018) <doi:10.21105/joss.00606>).
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coalition-probabilitieselection-analysiselections
6.59 score 22 stars 101 scripts 504 downloads