Penalized joint models of high-dimensional longitudinal biomarkers and a survival outcome
Author:
Affiliation:
1. Division of Epidemiology and Biostatistics, University of Illinois Chicago
Publisher
Institute of Mathematical Statistics
Reference52 articles.
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3. TAYLOR, J. M. G., PARK, Y., ANKERST, D. P., PROUST-LIMA, C., WILLIAMS, S., KESTIN, L., BAE, K., PICKLES, T. and SANDLER, H. (2013). Real-time individual predictions of prostate cancer recurrence using joint models. Biometrics 69 206–213.
4. BIEN, J. and TIBSHIRANI, R. J. (2011). Sparse estimation of a covariance matrix. Biometrika 98 807–820.
5. ANDRINOPOULOU, E.-R. and RIZOPOULOS, D. (2016). Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures. Stat. Med. 35 4813–4823.
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