Real.1: Real Dataset #1: Clinical Dataset ($p < n$ case)
Description
Publicly available dataset from the Women's Interagency HIV cohort Study (WIHS).
Inclusion criteria of the study were that women at enrolment were
(i) alive, (ii) HIV-1 infected, and (iii) free of clinical AIDS symptoms.
Women were followed until the first of the following occurred:
(i) treatment initiation (HAART), (ii) AIDS diagnosis, (iii) death, or administrative censoring.
The studied outcomes were the competing risks "AIDS/Death (before HAART)" and "Treatment Initiation (HAART)".
However, here, for simplification purposes, only the first of the two competing events (i.e. the time to AIDS/Death),
was used in this dataset example. Likewise, the entire study enrolled 1164 women, but only the complete cases were used
in this clinical dataset example for simplification. Variables included history of Injection Drug Use ("IDU") at enrollment,
African American ethnicity ("Race"), age ("Age"), and baseline CD4 count ("CD4"). The question in this dataset example
was whether it is possible to achieve a prognostication of patients for AIDS and HAART.
See below Bacon et al. (2005) and the WIHS website for more details.format
Dataset consists of a numeric data.frame containing $n=485$ complete observations (samples)
by rows and $p=4$ clinical covariates by columns, not including the censoring indicator and (censored) time-to-event variables.
It comes as a compressed Rda data file.source
See real data application in Dazard et al., 2015.References
- Dazard J-E., Choe M., LeBlanc M. and Rao J.S. (2015).
"Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods."
(Submitted).
- Dazard J-E., Choe M., LeBlanc M. and Rao J.S. (2014).
"Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods."
In JSM Proceedings, Survival Methods for Risk Estimation/Prediction Section. Boston, MA, USA.
American Statistical Association IMS - JSM, p. 3366-3380.
- Dazard J-E. and J. S. Rao (2010).
"Local Sparse Bump Hunting."
J. Comp Graph. Statistics, 19(4):900-92.
- Bacon M.C, von Wyl V., Alden C. et al. {2005}.
"Semi-Supervised Methods to Predict Patient Survival from Gene Expression Data."
Clin Diagn Lab Immunol 12(9): 1013-1019.
See Also
http://statepiaps.jhsph.edu/wihs/