get_sim_ci

<p>These helpers draw the simulated hazard trajectories once for the whole
(possibly grouped) <code>newdata</code> via <code>sim_hazard</code> -- so one set
of draws is shared across groups -- and then summarise them into pointwise
quantile intervals. Cumulative quantities are accumulated within each group
of <code>newdata</code>.</p>

internal

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.

Andreas Bender

pammtools

Piece-Wise Exponential Additive Mixed Modeling Tools for
Survival Analysis

Fabian Scheipl

Johannes Piller

Philipp Kopper

Lukas Burk

get_sim_ci function

Calculate simulation based confidence intervals — get_sim_ci

Calculate simulation based confidence intervals

get_sim_ci: Calculate simulation based confidence intervals

Description

Usage

Arguments