tidyr_verbs

fill

fill_

fill.ped

fill.nested_fdf

an object of class <code>ped</code>, see <code><a rd-options="" href="/link/as_ped?package=pammtools&version=0.1.14" data-mini-rdoc="pammtools::as_ped">as_ped</a></code>.

data

A selection of columns. If empty, nothing happens. You can
supply bare variable names, select all variables between <code>x</code> and <code>z</code>
with <code>x:z</code>, exclude <code>y</code> with <code>-y</code>. For more selection options, see the
<code><a rd-options="dplyr:select" href="/link/dplyr%3A%3Aselect()?package=pammtools&version=0.1.14&to=dplyr%3Aselect" data-mini-rdoc="dplyr:select::dplyr::select()">dplyr::select()</a></code> documentation.

Direction in which to fill missing values. Currently
either "down" (the default), "up", "downup" (i.e. first down and then up)
or "updown" (first up and then down).

.direction

conserve attributes? defaults to <code>TRUE</code>.

keep_attributes

See <code>tidyr</code> documentation of the respective functions for
 description and examples.

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.

Andreas Bender

pammtools

Piece-Wise Exponential Additive Mixed Modeling Tools for
Survival Analysis

Fabian Scheipl

tidyr_verbs function

an object of class <code>ped</code>, see <code><a rd-options='' href='as_ped'>as_ped</a></code>.

A selection of columns. If empty, nothing happens. You can
supply bare variable names, select all variables between <code>x</code> and <code>z</code>
with <code>x:z</code>, exclude <code>y</code> with <code>-y</code>. For more selection options, see the
<code><a rd-options='dplyr:select' href='dplyr::select()'>dplyr::select()</a></code> documentation.

tidyr_verbs: `tidyr` Verbs for `ped`-Objects

Description

Usage

Arguments

Value