SurvExpand function

Convert a data frame of non-equal interval continuous observations into equal interval continuous observations

Convert a data frame of non-equal interval continuous observations into equal interval continuous observations

SurvExpand convert a data frame of non-equal interval continuous observations into equal interval continuous observations. This is useful for creating time-interactions with tvc.

SurvExpand( data, GroupVar, Time, Time2, event, PartialData = TRUE, messages = TRUE )

Arguments

  • data: a data frame.
  • GroupVar: a character string naming the unit grouping variable.
  • Time: a character string naming the variable with the interval start time.
  • Time2: a character string naming the variable with the interval end time.
  • event: a character string naming the event variable. Note: must be numeric with 0 indicating no event.
  • PartialData: logical indicating whether or not to keep only the expanded data required to find the Cox partial likelihood.
  • messages: logical indicating if you want messages returned while the function is working.

Returns

Returns a data frame where observations have been expanded into equally spaced time intervals.

Details

The function primarily prepares data from the creation of accurate time-interactions with the tvc command. Note: the function will work best if your original time intervals are recorded in whole numbers. It also currently does not support repeated events data.

Examples

# Load Golub & Steunenberg (2007) Data data("GolubEUPData") # Subset PURELY TO SPEED UP THE EXAMPLE GolubEUPData <- GolubEUPData[1:500, ] # Expand data GolubEUPDataExpand <- SurvExpand(GolubEUPData, GroupVar = 'caseno', Time = 'begin', Time2 = 'end', event = 'event')

References

Gandrud, Christopher. 2015. simPH: An R Package for Illustrating Estimates from Cox Proportional Hazard Models Including for Interactive and Nonlinear Effects. Journal of Statistical Software. 65(3)1-20.

See Also

tvc

  • Maintainer: Christopher Gandrud
  • License: GPL-3
  • Last published: 2021-01-10