A data frame contains data on recurrences of bladder cancer, used by many people to demonstrate methodology for recurrent event modeling. The data was obtained by courtesy of Ying Zhang, containing records of 118 patients from three treatment arms: 48 are from the placebo arm, 37 are from the thiotepa arm, and the rest 33 are from the pyridoxine arm.
data.frame contains the following columns:
cumulative number of tumors
number of new tumors since last observation time
initial number of tumors (8=8 or more)
size (cm) of largest initial tumor
dummy variable for pyridoxine arm
dummy variable for thiotepa arm
To our surprise, the two-treatment (placebo and thiotepa) subset of
the full version
bladTumor do not match the two-treatment
Byar, D. P. (1980). The Veterans administration study of chemoprophylaxis for recurrent stage I bladder tumors: Comparisons of placebo, pyridoxine, and topical thiotepa. Bladder Tumors and Other Topics in Urological Oncology, pp. 363--370. New York: Plenum.
Wellner, J. A. and Zhang, Y. (2007) Two likelihood-based semiparametric estimation methods for panel count data with covariates. Annals of Statistics, 35(5), 2106--2142.
Lu, M., Zhang, Y. and Huang, J. (2009) Semiparametric estimation methods for panel count data using monotone B-Splines. Journal of the American Statistical Association 104(487), 1060--1070.
data(bladTumor) ## Plot bladder tumor data p <- plot(with(bladTumor, PanelSurv(subject, time, count2))) print(p)