A data frame contains data on recurrences of bladder cancer,
used by many people to demonstrate methodology for recurrent event modelling.
This data set organized differently from bladTumor
.
The data contains records of 85 patients from two treatment arms:
48 are from the placebo arm, and the rest 37 are from the thiotepa arm.
data(blaTum)
A data.frame
contains the following columns:
id
patient id
treatment
placebo = 0, thiotepa = 1
size
size (cm) of largest initial tumor
num
initial number of tumors (8 = 8 or more)
time
observation time
count
number of new tumors since last observation time
To our surprise, the two-treatment (placebo and thiotepa) subset of
the full version bladTumor
do not match the two-treatment version blaTum
.
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.
Sun, J. and Wei, L. J. (2000) Regression analysis of panel count data with covariate dependent observation and censoring times. Journal of the Royal Statistical Society, Series B: Statistical Methodology, 62(2), 293--302.
Huang, C. Y., Wang, M. C. and Zhang, Y. (2006). Analyzing panel count data with informative observation times. Biometrika, 93(4): 763--776.
data(blaTum) library(ggplot2) ggplot(blaTum, aes(time, id)) + geom_tile(aes(fill=count)) + facet_grid(treatment ~ ., scales="free_y", )