BrainCancer: Brain Cancer Data
In ISLR2: Introduction to Statistical Learning, Second Edition
BrainCancer R Documentation
Brain Cancer Data
Description
A
data set consisting of survival times for patients diagnosed with brain cancer.
Usage
BrainCancer
Format
A data frame with 88 observations and 8 variables:
sexFactor with levels "Female" and "Male"
diagnosisFactor with levels "Meningioma",
"LG glioma", "HG glioma", and "Other".
locLocation factor with levels "Infratentorial" and "Supratentorial".
kiKarnofsky index.
gtvGross tumor volume, in cubic centimeters.
stereoStereotactic method factor with levels "SRS"
and "SRT".
statusWhether the patient is still alive at the end of the study: 0=Yes, 1=No.
timeSurvival time, in months.
Source
I. Selingerova, H. Dolezelova, I. Horova, S. Katina, and J. Zelinka.
Survival of patients with primary brain tumors: Comparison of two
statistical approaches. PLoS One, 11(2):e0148733, 2016. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749663/
References
James, G., Witten, D., Hastie, T., and Tibshirani, R. (2021)
An Introduction to Statistical Learning with applications in R,
Second Edition,
https://www.statlearning.com,
Springer-Verlag, New York
ISLR2 documentation built on Nov. 20, 2022, 1:06 a.m.
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| BrainCancer | R Documentation |
Brain Cancer Data
Description
A data set consisting of survival times for patients diagnosed with brain cancer.
Usage
BrainCancer
Format
A data frame with 88 observations and 8 variables:
sexFactor with levels "Female" and "Male"
diagnosisFactor with levels "Meningioma", "LG glioma", "HG glioma", and "Other".
locLocation factor with levels "Infratentorial" and "Supratentorial".
kiKarnofsky index.
gtvGross tumor volume, in cubic centimeters.
stereoStereotactic method factor with levels "SRS" and "SRT".
statusWhether the patient is still alive at the end of the study: 0=Yes, 1=No.
timeSurvival time, in months.
Source
I. Selingerova, H. Dolezelova, I. Horova, S. Katina, and J. Zelinka. Survival of patients with primary brain tumors: Comparison of two statistical approaches. PLoS One, 11(2):e0148733, 2016. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749663/
References
James, G., Witten, D., Hastie, T., and Tibshirani, R. (2021) An Introduction to Statistical Learning with applications in R, Second Edition, https://www.statlearning.com, Springer-Verlag, New York
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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