Survival data measured in 1200 HIV positive patients. Start of follow-up is HIV seroconversion. Each row corresponds to a 100 day interval of follow-up time, using the counting process notation. Patients can initiate HAART therapy. CD4 count is a confounder for the effect of HAART on mortality.
data(haartdat)A data frame with 1200 patients and multiple observations per patient (counting process notation) on the following 8 variables:
Patient ID.
Starting time for each interval of follow-up, measured in days since HIV seroconversion.
End time for each interval of follow-up, measured in days since HIV seroconversion.
Indicator for the initiation of HAART therapy at the end of the interval (0 = HAART not initiated / 1 = HAART initiated).
Indicator for death at the end of the interval (0 = alive / 1 = died).
Sex (0 = male / 1 = female).
Age at the start of follow-up (years).
Square root of CD4 count, measured at fuptime,
before haartind.
The final observed time point for the individual.
Indicator for dropout/censoring at the end of the interval (0 = no, 1 = yes).
Willem M. van der Wal willem@vanderwalresearch.com, Ronald B. Geskus rgeskus@oucru.org
These data were simulated to demonstrate Inverse Probability Weighting (IPW).
To allow for models predicting the initiation of HAART at fuptime = 0,
the starting time for the first interval of each patient is set to -100.
Van der Wal W.M. & Geskus R.B. (2011). ipw: An R Package for Inverse Probability Weighting. Journal of Statistical Software, 43(13), 1-23. tools:::Rd_expr_doi("10.18637/jss.v043.i13").
basdat, ipwplot, ipwpoint,
ipwtm, timedat, tstartfun
# For a full example of how to use this data with ipwtm, see:
# ?ipwtm
Run the code above in your browser using DataLab