processSurvData: Process survival data to calculate survival curves

In nuno-agostinho/psichomics: Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation

Process survival data to calculate survival curves

Description

Process survival data to calculate survival curves

Usage

processSurvData(
  event,
  timeStart,
  timeStop,
  followup,
  group,
  clinical,
  survTime = NULL
)

Arguments

event	Character: name of column containing time of the event of interest
timeStart	Character: name of column containing starting time of the interval or follow up time
timeStop	Character: name of column containing ending time of the interval (only relevant for interval censoring)
followup	Character: name of column containing follow up time
group	Character: group relative to each subject
clinical	Data frame: clinical data
survTime	survTime object: Times to follow up, time start, time stop and event (optional)

Details

The event time is only used to determine whether the event has occurred (1) or not (0) in case of missing values.

If survTime = NULL, survival times are obtained from the clinical dataset according to the names given in timeStart, timeStop, event and followup. This may become quite slow when used in a loop. If the aforementioned variables are constant, consider running getAttributesTime() outside the loop and using its output via the survTime argument of this function (see Examples).

Value

Data frame with terms needed to calculate survival curves

nuno-agostinho/psichomics documentation built on Feb. 11, 2024, 11:16 p.m.