TY - JOUR
T1 - Constructing multivariate survival trees
T2 - The MST package for R
AU - Calhoun, Peter
AU - Su, Xiaogang
AU - Nunn, Martha
AU - Fan, Juanjuan
N1 - Funding Information:
This research was supported in part by the National Institutes of Health grant R01-DE019656. We thank Ms. Nici Kimmes, DDS for her help in extracting the data from AxiUm.
Publisher Copyright:
© 2018, American Statistical Association. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.
AB - Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.
UR - http://www.scopus.com/inward/record.url?scp=85042696294&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85042696294&partnerID=8YFLogxK
U2 - 10.18637/jss.v083.i12
DO - 10.18637/jss.v083.i12
M3 - Article
AN - SCOPUS:85042696294
SN - 1548-7660
VL - 83
JO - Journal of Statistical Software
JF - Journal of Statistical Software
ER -