make_data_multi_state {survHE}

make_data_multi_state

Description

Takes as input an individual-level dataset including data on both progression and death time (jointly) and manipulates it using dplyr functions to create a full "multi-state" dataset, in which all the transitions are tracked. This can then be used to fit survival models and compute all the estimates for the whole set of transition probabilities

Usage

make_data_multi_state(
  data,
  id = "id",
  prog = "prog",
  death = "death",
  prog_t = "prog_t",
  death_t = "death_t",
  keep = NULL,
  ...
)

Arguments

data

dataset containing the full ILD with information on both progression and death. Can be a data.frame or a tibble

id

The column with the individual identifier. Can be NULL (in which case, it will be created from scratch)

prog

The progression indicator: takes value 1 if the individual has progressed and 0 otherwise. Defaults to the column named 'prog' in the dataset

death

The death indicator: takes value 1 if the individual has died and 0 otherwise. Defaults to the column named 'death' in the dataset

prog_t

The progression time. Defaults to the column named 'prog_t' in the dataset

death_t

The death time. Defaults to the column named 'death_t' in the dataset

keep

A vector of strings with the names of the additional variables from the original dataset to keep into the multistate dataset. If 'NULL' (default), then keeps all

...

additional arguments.

Value

A tibble containing the event history for each individual and with the following variables: id = Patients ID; from = Initial state (1=Pre-progression, 2=Progression, 3=Death); to = End state (1=Pre-progression, 2=Progression, 3=Death); trans = Transition ID: 1=Pre-progression -> Progression; 2=Pre-Progression -> Death; 3=Progression -> Death; Tstart = Entry time (either entry or progression); Tstop = Exit time (time of event or censoring time); status = Event indicator (1=yes, 0=censored), for the specific event under consideration; treat = Treatment indicator All the other original variables are appended to these, but can be removed

Note

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Author(s)

Gianluca Baio

References

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See Also

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Examples

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