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pammtools: Piece-Wise Exponential Additive Mixed Modeling Tools

Installation

Install from CRAN or GitHub using:

# CRAN
install.packages("pammtools")

# GitHub
devtools::install_github("adibender/pammtools")

Overview

pammtools facilitates the estimation of Piece-wise exponential Additive Mixed Models (PAMMs) for time-to-event data. PAMMs can be represented as generalized additive models and can therefore be estimated using GAM software (e.g. mgcv), which, compared to other packages for survival analysis, often offers more flexibility w.r.t. to the specification of covariate effects (e.g. non-linear, time-varying effects, cumulative effects, etc.).

To get started, see the Articles section.

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Version

Install

install.packages('pammtools')

Monthly Downloads

3,693

Version

0.2.3

License

MIT + file LICENSE

Issues

17

Pull Requests

2

Stars

49

Forks

10

Maintainer

Andreas Bender

Last Published

May 27th, 2020

Functions in pammtools (0.2.3)

add_hazard

Add predicted (cumulative) hazard to data set
as.data.frame.crps

Transform crps object to data.frame
combine_df

Create a data frame from all combinations of data frames
as_ped

Transform data to Piece-wise Exponential Data (PED)
add_tdc

Add time-dependent covariate to a data set
add_surv_prob

Add survival probability estimates
combine_cut

Extract unique cut points when time-dependent covariates present
calc_ci

Calculate confidence intervals
add_term

Embeds the data set with the specified (relative) term contribution
compute_cumu_diff

Calculate difference in cumulative hazards and respective standard errors
geom_stepribbon

Step ribbon plots.
get_cumu_eff

Calculate (or plot) cumulative effect for all time-points of the follow-up
get_intervals

Information on intervals in which times fall
get_laglead

Construct or extract data that represents a lag-lead window
extub_event

Time until extubation
get_terms

Extract the partial effects of non-linear model terms
gg_re

Plot Normal QQ plots for random effects
gg_slice

Plot 1D (smooth) effects
pammtools

pammtools: Piece-wise exponential Additive Mixed Modeling tools.
get_lhs_vars

Extract variables from the left-hand-side of a formula
geom_hazard

(Cumulative) (Step-) Hazard Plots.
fcumu

A formula special used to handle cumulative effect specifications
get_plotinfo

Extract plot information for all special model terms
dplyr_verbs

dplyr Verbs for ped-Objects
get_sim_ci

Calculate simulation based confidence intervals
gg_fixed

Forrest plot of fixed coefficients
gg_partial

Visualize effect estimates for specific covariate combinations
make_time_mat

Create matrix components for cumulative effects
gg_laglead

Plot Lag-Lead windows
get_ped_form

Extract variables from the left-hand-side of a formula
get_surv_prob

Calculate survival probabilities
patient

Survival data of critically ill ICU patients
get_cumu_coef

Extract cumulative coefficients (cumulative hazard differences)
get_tdc

Extract time-dependent covariates from data set
get_cut

Obtain interval break points
modus

Calculate the modus
tidy_smooth

Extract 1d smooth objects in tidy data format.
make_newdata

Construct a data frame suitable for prediction
split_data

Function to transform data without time-dependent covariates into piece-wise exponential data format
gg_smooth

Plot smooth 1d terms of gam objects
daily

Time-dependent covariates of the patient data set.
get_tdc_form

Extract variables from the left-hand-side of a formula
tidy_smooth2d

Extract 2d smooth objects in tidy format.
ped_info

Extract interval information and median/modus values for covariates
get_cumu_hazard

Calculate cumulative hazard
%>%

Pipe operator
nest_tdc

Create nested data frame from data with time-dependent covariates
get_cumulative

Expand time-dependent covariates to functionals
get_tdc_vars

Extract variables from the left-hand-side of a formula
get_hazard

Calculate predicted hazard
has_tdc

Extract time-dependent covariates from data set
predictSurvProb.pamm

S3 method for pamm objects for compatibility with package pec
prep_concurrent

Extract information on concurrent effects
pamm

Fit a piece-wise exponential additive model
get_term

Extract partial effects for specified model terms
tidyr_verbs

tidyr Verbs for ped-Objects
gg_tensor

Plot tensor product effects
simdf_elra

Simulated data with cumulative effects
rpexp

Draw random numbers from piece-wise exponential distribution.
seq_range

Generate a sequence over the range of a vector
int_info

Create start/end times and interval information
sample_info

Extract information of the sample contained in a data set
tumor

Stomach area tumor data
tidy_re

Extract random effects in tidy data format.
sim_pexp

Simulate survival times from the piece-wise exponential distribution
warn_about_new_time_points

Warn if new t_j are used
cumulative

Formula specials for defining time-dependent covariates
tidy_fixed

Extract fixed coefficient table from model object