rott2: Cohort study on breast cancer patients from the Netherlands.
In AF: Model-Based Estimation of Confounder-Adjusted Attributable Fractions

Description Usage Format References

This dataset is borrowed from "Flexible parametric survival analysis using Stata: beyond the Cox model" (Roystone and Lambert, 2011). It contains follow-up data on 2982 woman with breast cancer who have gone through breast surgery. The women are followed from the time of surgery until death, relapse or censoring.

1	data(rott2)

The dataset rott2 contains the following variables:

pid: patient ID number.
year: year of breast surgery (i.e. year of enrollment into the study), between the years 1978-1993.
rf: relapse free interval measured in months.
rfi: relapse indicator.
m: metastasis free.
mfi: metastasis status.
os: overall survival
osi: overall survival indicator
age: age at surgery measured in years.
meno: menopausal status with levels "pre" and "post".
size: tumor size in three classes: <=20mm, >20-50mmm and >50mm.
grade: differentiation grade with levels 2 or 3.
pr: progesterone receptors, fmol/l.
er: oestrogen receptors, fmol/l.
nodes: the number of positive lymph nodes.
hormon: hormonal therapy with levels "no" and "yes".
chemo: categorical variable indicating whether the patient recieved chemotheraphy or not, with levels "no" and "yes".
recent: a numeric indicator of whether the tumor was discovered recently with levels "1978-87" and "1988-93".
no.chemo: a numerical indicator of whether the patient did not recieved chemotherapy. Recoded version of "chemo" where "yes" is recoded as 0 and "no" is recoded as 1.

The following changes have been made to the original data in Roystone and Lambert (2011):

- The variable "chemo" is recoded into the numeric indicator variable "no.chemo":

rott22$no.chemo <- as.numeric(rott2$chemo == "no")

The follwing variables have been removed from the original dataset: enodes, pr_1, enodes_1, _st, _d, _t, _t0 since they are recodings of some existing variables which are not used in this analysis.

Royston, Patrick & Lambert, Paul. C (2011). Flexible parametric survival analysis using Stata: beyond the Cox model. College Station, Texas, U.S, Stata press.

http://www.stata-press.com/data/fpsaus.html

AF documentation built on May 21, 2019, 1:01 a.m.