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Li, G.R., Lian, H., Feng, S.Y. and Zhu, L.X. (2013) Automatic Variable Selection for Longitudinal Generalized Linear Models. Computational Statistics and Data Analysis, 61, 174-186.
http://dx.doi.org/10.1016/j.csda.2012.12.015

has been cited by the following article:

• TITLE: Automatic Variable Selection for Single-Index Random Effects Models with Longitudinal Data

  AUTHORS: Suigen Yang, Liugen Xue

  KEYWORDS: Variable Selection; Single-Index Model; Random Effects; Longitudinal Data

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.3, April 24, 2014

  ABSTRACT: We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method shares some of the desired features of existing variable selection methods: the resulting estimator enjoys the oracle property; the proposed procedure avoids the convex optimization problem and is flexible and easy to implement. Moreover, we use the penalized weighted deviance criterion for a data-driven choice of the tuning parameters. Simulation studies are carried out to assess the performance of our method, and a real dataset is analyzed for further illustration.