Fast FSR variable selection with applications to clinical trials

Biometrics

Volumn 65, Issue 3, 2009, Pages 692-700

  Boos, Dennis D ^a   Stefanski, Leonard A ^a   Wu, Yujun ^b  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b SANOFI   (France)

Author keywords

Bagging; False discovery rate; False selection rate; Forward selection; LASSO; Model error; Model selection; Regression

Indexed keywords

BIOMETRICS;

BAGGING; CLINICAL TRIAL; FALSE DISCOVERY RATE; FALSE SELECTION RATE; FORWARD SELECTION; LASSO; MODEL ERRORS; MODEL SELECTION; REGRESSION; VARIABLES SELECTIONS;

REGRESSION ANALYSIS;

MODELING; REGRESSION ANALYSIS; TESTING METHOD;

ARTICLE; CLINICAL TRIAL; COVARIANCE; LINEAR REGRESSION ANALYSIS; LOGISTIC REGRESSION ANALYSIS; OUTCOME VARIABLE; PREDICTION; PROPORTIONAL HAZARDS MODEL; RANDOM SAMPLE; SAMPLE SIZE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL;

BIOMETRY; CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; EFFECT MODIFIERS (EPIDEMIOLOGY); MODELS, STATISTICAL; PROPORTIONAL HAZARDS MODELS; REGRESSION ANALYSIS;

EID: 70349251735     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2008.01127.x     Document Type: Article

References (18)

1. Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B 57, 289 300.
2. Benjamini, Y. and Hochberg, Y. (2000). On the adaptive control of the false discovery rate in multiple testing with independent statistics. Journal of Educational and Behavioral Statistics 25, 60 83.
3. Benjamini, Y. and Yekutieli, D. (2001). The control of the the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165 1188.
4. Benjamini, Y., Krieger, A. M., and Yekutieli, D. (2006). Adaptive linear step-up procedures that control the false discovery rate. Biometrika 93, 491 507.
5. Breiman, L. (1996a). Heuristics of instability and stabilization in model selection. The Annals of Statistics 24, 2350 2383.
6. Breiman, L. (1996b). Bagging predictors. Machine Learning 24, 123 140.
7. Buckley, J. and James, I. (1979). Linear regression with censored data. Biometrika 66, 429 436.
8. Bunea, F., Wegkamp, M. H., and Auguste, A. (2006). Consistent variable selection in high dimensional regression via multiple testing. Journal of Statistical Planning and Inference 136, 4349 4364.
9. Hammer, S. M., Katzenstein, D. A., Hughes, M. D., Gundaker, H., Schooley, R. T., Haubrich, R. H., Henry, W. K., Lederman, M. M., Phair, J. P., Niu, M., Hirsch, M. S., and Merigan, T. C., for the Aids Clinical Trials Group Study 175 Study Team 1996). A trial comparing nucleoside monotherapy with combination therapy in HIV-infected adults with CD4 counts from 200 to 500 per cubic millimeter. The New England Journal of Medicine 333, 1081 1089.
10. Harrington, R. A. for the PURSUIT Trial Investigators 1998). Inhibition of platelet glycoprotein with eptifibatide in patients with acute coronary syndromes. The New England Journal of Medicine 339, 436 443.
11. Johnson, B. A. (2008). Variable selection in semiparametric linear regression with censored data. Journal of the Royal Statistic Society, Series B. 70, 351 370.
12. Lu, X. and Tsiatis, A. A. (2008). Improving the efficiency of the log-rank test using auxiliary covariates. Biometrika 95, 679 694.
13. Tibshirani, R. J. (1996). Regression shrinkage and selection via the LASSO. Journal of the Royal Statistic Society, Series B 58, 267 288.
14. Tsiatis, A. A., Davidian, M., Zhang, M., and Lu, X. (2008). Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: A principled yet flexible approach. Statistics in Medicine 29, 4658 4677.
15. Wang, H. and Leng, C. (2007). Unified LASSO estimation via least squares approximation. Journal of the American Statistical Association 102, 1039 1048.
16. Wu, Y. (2004). Controlling variable selection by the addition of pseudovariables. Unpublished doctoral thesis. Statistics Department, North Carolina State University.
17. Wu, Y., Boos, D. D., and Stefanski, L. A. (2007). Controlling variable selection by the addition of pseudovariables. Journal of the American Statistical Association 102, 235 243.
18. Yuan, Z. and Yang, Y. (2005). Combining linear regression models: When and how Journal of the American Statistical Association 100, 1202 1214.