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(bladTumor)

Format

A data.frame contains the following columns:

subject

patient id

time

observation time

count

cumulative number of tumors

count2

number of new tumors since last observation time

number

initial number of tumors (8=8 or more)

size

size (cm) of largest initial tumor

pyridoxine

dummy variable for pyridoxine arm

thiotepa

dummy variable for thiotepa arm

Note

To our surprise, the two-treatment (placebo and thiotepa) subset of the full version bladTumor do not match the two-treatment version blaTum.

References

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.

See also

Examples

data(bladTumor) ## Plot bladder tumor data p <- plot(with(bladTumor, PanelSurv(subject, time, count2))) print(p)