Description Usage Format Note References See Also Examples
A data frame contains data on recurrences of bladder cancer, used by many people to demonstrate methodology for recurrent event modelling. 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.
1 |
subject
: patient id
time
: observation time
count
: cumulative number of tumors
count2
: number of new tumors since last observation time
number
: initial number of tumours (8=8 or more)
size
: size (cm) of largest initial tumour
pyridoxine
: dummy variable for pyridoxine arm
thiotepa
: 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
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.
Wellner, J. A. and Zhang, Y. (2007) Two likelihood-based semiparametric estimation methods for panel count data with covariates. Annals of Statistics, 35 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 1060–1070.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Load data set
data(bladTumor)
# Plot bladder tumor data
p <- plot(with(bladTumor, PanelSurv(subject, time, count2)))
print(p)
## Not run:
# Fit a semiparametric regression model
formula <- PanelSurv(subject, time, count2) ~ number + size + pyridoxine + thiotepa
panelReg(formula, data=bladTumor, method="MPL", se="Bootstrap", control=list(R=20))
panelReg(formula, data=bladTumor, method="MLs", se="Bootstrap", control=list(R=20))
## End(Not run)
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