# haartdat

##### HAART and Survival in HIV Patients

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.

- Keywords
- datasets

##### Usage

`data(haartdat)`

##### Details

These data were simulated.

Patients can initiate HAART at `fuptime=0`

. Therefore, to allow the fitting of a model predicting initiation of HAART, starting time for the first interval within each patient is negative (-100).

##### Format

`patient`

- patient ID
`tstart`

- starting time for each interval of follow-up, measured in days since HIV seroconversion
`fuptime`

- end time for each interval of follow-up, measured in days since HIV seroconversion
`haartind`

- indicator for the initiation of HAART therapy at the end of the interval (0=HAART not initiated/1=HAART initiated).
`event`

- indicator for death at the end of the interval (0=alive/1=died)
`sex`

- sex (0=male/1=female)
`age`

- age at the start of follow-up (years)
`cd4.sqrt`

- square root of CD4 count, measured at fuptime, before
`haartind`

##### References

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. http://www.jstatsoft.org/v43/i13/.

##### See Also

`basdat`

, `haartdat`

, `ipwplot`

, `ipwpoint`

, `ipwtm`

, `timedat`

, `tstartfun`

.

##### Examples

```
#see ?ipwtm for example
```

*Documentation reproduced from package ipw, version 1.0-11, License: GPL (>= 2)*