A leave-one-out cross-validation SAS macro for the identification of markers associated with survival.
Publication
, Journal Article
Rushing, C; Bulusu, A; Hurwitz, HI; Nixon, AB; Pang, H
Published in: Comput Biol Med
February 2015
A proper internal validation is necessary for the development of a reliable and reproducible prognostic model for external validation. Variable selection is an important step for building prognostic models. However, not many existing approaches couple the ability to specify the number of covariates in the model with a cross-validation algorithm. We describe a user-friendly SAS macro that implements a score selection method and a leave-one-out cross-validation approach. We discuss the method and applications behind this algorithm, as well as details of the SAS macro.
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Published In
Comput Biol Med
DOI
EISSN
1879-0534
Publication Date
February 2015
Volume
57
Start / End Page
123 / 129
Location
United States
Related Subject Headings
- Survival Analysis
- Reproducibility of Results
- Prognosis
- Humans
- Computer Simulation
- Computational Biology
- Clinical Trials as Topic
- Biomedical Engineering
- Biomarkers
- Algorithms
Citation
APA
Chicago
ICMJE
MLA
NLM
Rushing, C., Bulusu, A., Hurwitz, H. I., Nixon, A. B., & Pang, H. (2015). A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. Comput Biol Med, 57, 123–129. https://doi.org/10.1016/j.compbiomed.2014.11.015
Rushing, Christel, Anuradha Bulusu, Herbert I. Hurwitz, Andrew B. Nixon, and Herbert Pang. “A leave-one-out cross-validation SAS macro for the identification of markers associated with survival.” Comput Biol Med 57 (February 2015): 123–29. https://doi.org/10.1016/j.compbiomed.2014.11.015.
Rushing C, Bulusu A, Hurwitz HI, Nixon AB, Pang H. A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. Comput Biol Med. 2015 Feb;57:123–9.
Rushing, Christel, et al. “A leave-one-out cross-validation SAS macro for the identification of markers associated with survival.” Comput Biol Med, vol. 57, Feb. 2015, pp. 123–29. Pubmed, doi:10.1016/j.compbiomed.2014.11.015.
Rushing C, Bulusu A, Hurwitz HI, Nixon AB, Pang H. A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. Comput Biol Med. 2015 Feb;57:123–129.
Published In
Comput Biol Med
DOI
EISSN
1879-0534
Publication Date
February 2015
Volume
57
Start / End Page
123 / 129
Location
United States
Related Subject Headings
- Survival Analysis
- Reproducibility of Results
- Prognosis
- Humans
- Computer Simulation
- Computational Biology
- Clinical Trials as Topic
- Biomedical Engineering
- Biomarkers
- Algorithms