REFERENCES
- Andersen, P.K., Klein, J.P., Knudsen, K., Palacios, R.T. (1997), Estimation of Variance in Cox’s Regression Model With Shared Gamma Frailties, Biometrics, 53, 1475–1484.
- Androulakis, E., Koukouvinos, C., Vonta, F. (2012), Estimation and Variable Selection via Frailty Models With Penalized Likelihood, Statistics in Medicine, 31, 2223–2239.
- Breslow, N.E. (1972), Discussion of “Regression Models and Life Tables” by D.R. Cox, Journal of the Royal Statistical Society, Series B, 34, 216–217.
- Cai, J., Fan, J., Li, R., Zhou, H. (2005), Variable Selection for Multivariate Failure Time Data, Biometrika, 92, 303–316.
- Casella, G. (1985), An Introduction to Empirical Bayes Data Analysis, The American Statistician, 39, 83–87.
- Charalambous, C., Pan, J., Tranmer, M. (2014), Variable Selection in Joint Modelling of Mean and Variance via H-Likelihood, Statistical Modelling: An International Journal (to appear).
- Cox, D.R. (1972), “Regression Models and Life Tables” (with discussion), Journal of the Royal Statistical Society, Series B, 74, 187–220.
- Duchateau, L., and Janssen, P. (2008), The Frailty Model, New York: Springer-Verlag.
- Efron, B., Morris, C. (1975), Data Analysis Using Stein’s Estimator and Its Generalizations, Journal of the American Statistical Association, 70, 311–319.
- Ettinger, D.S., Finkelstein, D.M., Abeloff, M.D., Ruckdeschel, J.C., Aisner, S.C., and Eggleston, J.C. (1990), A Randomized Comparison of Standard Chemotherapy Versus Alternating Chemotherapy and Maintenance Versus no Maintenance Therapy for Extensive-Stage Small-Cell Lung Cancer: A Phase Iii Study of the Eastern Cooperative Oncology Group, Journal of Clinical Oncology, 8, 230–240.
- Fan, J., Li, R. (2001), Variable Selection Via Nonconcave Penalized Likelihood and Its Oracle Properties, Journal of the American Statistical Association, 96, 1348–1360.
- ——— (2002), Variable Selection for Cox’s Proportional Hazards Model and Frailty Model, The Annals of Statistics, 30, 74–99.
- Fan, J., Lv, J. (2010), A Selective Overview of Variable Selection in High Dimensional Feature Space, Statistica Sinica, 20, 101–148.
- Fan, J., Peng, H. (2004), Nonconcave Penalized Likelihood With a Diverging Number of Parameters, The Annals of Statistics, 32, 928–961.
- Fleming, T.R., and Harrington, D.P. (1991), Counting Processes and Survival Analysis, New York: Wiley.
- Gray, R.J. (1994), A Bayesian Analysis of Institutional Effects in Multicenter Cancer Clinical Trial, Biometrics, 50, 244–253.
- Ha, I.D., Lee, Y. (2003), Estimating Frailty Models via Poisson Hierarchical Generalized Linear Models, Journal of Computational and Graphical Statistics, 12, 663–681.
- Ha, I.D., Lee, Y., MacKenzie, G. (2007), Model Selection for Multicomponent Frailty Models, Statistics in Medicine, 26, 4790–4807.
- Ha, I.D., Lee, Y., Song, J.K. (2001), Hierarchical Likelihood Approach for Frailty Models, Biometrika, 88, 233–243.
- Ha, I.D., Noh, M., Lee, Y. (2010), Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models, Scandinavian Journal of Statistics, 37, 307–320.
- Ha, I.D., Sylvester, R., Legrand, C., MacKenzie, G. (2011), Frailty Modelling for Survival Data From Multi-Centre Clinical Trials, Statistics in Medicine, 30, 2144–2159.
- Hunter, D., Li, R. (2005), Variable Selection Using MM Algorithms, The Annals of Statistics, 33, 1617–1642.
- Johnson, B.A., Lin, D.Y., Zeng, D. (2008), Penalized Estimating Functions and Variable Selection in Semiparametric Regression Models, Journal of the American Statistical Association, 103, 672–680.
- Kwon, S., Oh, S., Lee, Y. (2013), The Use of Random-Effect Models for High-Dimensional Variable Selection Problems, revision submitted to Scandinavian Journal of Statistics.
- Lee, D., Lee, W., Lee, Y., Pawitan, Y. (2010), Super Sparse Principal Component Analysis for High-Throughput Genomic Data, BMC Bioinformatics, 11, 296–305.
- ——— (2011a), Sparse Partial Least-Squares Regression and Its Applications to High-Throughput Data Analysis, Chemometrics and Intelligent Laboratory Systems, 109, 1–8.
- ——— (2011b), Sparse Canonical Covariance Analysis for High-Throughput Data, Statistical Applications in Genetics and Molecular Biology, 10, 1–24.
- Lee, Y., Nelder, J.A. (1996), “Hierarchical Generalized Linear Models” (with discussion), Journal of the Royal Statistical Society, Series B, 58, 619–678.
- ——— (2006), “Double Hierarchical Generalized Linear Models” (with discussion), Journal of the Royal Statistical Society, Series C, 55, 139–185.
- Lee, Y., Nelder, J.A., and Pawitan, Y. (2006), Generalised Linear Models With Random Effects: Unified Analysis via H-Likelihood, London: Chapman and Hall.
- Lee, Y., Oh, H.S. (2009), Random-Effect Models for Variable Selection, Technical Report No. 2009-4, 1–24, Department of Statistics, Stanford University.
- McGilchrist, C.A., Aisbett, C.W. (1991), Regression With Frailty in Survival Analysis, Biometrics, 47, 461–466.
- Noh, M., Ha, I.D., Lee, Y. (2006), Dispersion Frailty Models and HGLMs, Statistics in Medicine, 25, 1341–1354.
- Rondeau, V., Michiels, S., Liquet, B., Pignon, J.P. (2008), Investigating Trial and Treatment Heterogeneity in an Individual Patient Data Meta-Analysis of Survival Data by Means of the Penalized Maximum Likelihood Approach, Statistics in Medicine, 27, 1894–1910.
- Therneau, T.M., Grambsch, P.M., Pankratz, V.S. (2003), Penalized Survival Models and Frailty, Journal of Computational and Graphical Statistics, 12, 156–175.
- Tibshirani, R. (1996), Regression Shrinkage and Selection via the Lasso, Journal of the Royal Statistical Society, Series B, 58, 267–288.
- ——— (1997), The LASSO Method for Variable Selection in the Cox Model, Statistics in Medicine, 16, 385–395.
- Vaida, F., Xu, R. (2000), Proportional Hazards Model With Random Effects, Statistics in Medicine, 19, 3309–3324.
- Wang, H., Li, R., Tsai, C.L. (2007), Tuning Parameter Selectors for the Smoothly Clipped Absolute Deviation Method, Biometrika, 94, 553–568.
- Yau, K. K.W. (2001), Multilevel Models for Survival Analysis With Random Effects, Biometrics, 57, 96–102.
- Zhang, H.H., Lu, W. (2007), Adaptive Lasso for Cox’s Proportional Hazards Model, Biometrika, 94, 691–703.
- Zhang, Y., Li, R., Tsai, C.L. (2010), Regularization Parameter Selections via Generalized Information Criterion, Journal of the American Statistical Association, 105, 312–323.
- Zou, H. (2006), The Adaptive Lasso and Its Oracle Properties, Journal of the American Statistical Association, 101, 1418–1429.