get_tdc

A data frame (potentially) containing time-dependent covariates.

data

A character indicating the grouping variable. For each covariate
it will be checked if their values change within a group specified by
<code>id_var</code>.

id_var

For all covariates in the data set, this functions checks if the values
of the covariate changes per ID or other grouping variable. Returns the names
of variables that change over time.

internal

The Piece-wise exponential (Additive Mixed) Model
(PAMM; Bender and Scheipl (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 (2018) <doi: 10.1093/biostatistics/kxy003>.
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.

get_tdc: Extract time-dependent covariates from data set

Description

Usage

Arguments

Value