as_fped: Transform data with one row per subject to functional PED...

In adibender/pamm: Functions and Utilities for fitting Piece-wise Exponential (Additive) models

Description

Transform data with one row per subject to functional PED format

Usage

as_fped(formula, data, data_orig, cut = NULL, ..., max.end = FALSE,
  ll_fun = function(te, t) {     te <= t }, keep = c("id", "tstart",
  "eta_base", "eta_wce", "eta"))

Arguments

formula	a model formula
data	a data frame
cut	the vector of timepoints to cut at
...	Further arguments passed to survSplit
max.end	logical. Should the last interval span until the last observed censoring or event time (if larger than the largest specified cut point).
ll_fun	Function with two arguments that indicates how lag-lead matrix should be contructed. First argument is the time on the scale of the exposure, second argument is the time on the scale of the follow-up. Internally the lag lead matrix will be constructed by calling t(outer(te_vec, t_vec, ll_fun)).

Value

A data frame class ped in piece-wise exponential data format.

See Also

survSplit

adibender/pamm documentation built on May 14, 2019, 5:22 p.m.