Fixed and random effects selection by REML and pathwise coordinate optimization

Bingqing Lin, Zhen Pang, Jiming Jiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)

Abstract

We propose a two-stage model selection procedure for the linear mixed-effects models. The procedure consists of two steps: First, penalized restricted log-likelihood is used to select the random effects, and this is done by adopting a Newton-type algorithm. Next, the penalized log-likelihood is used to select the fixed effects via pathwise coordinate optimization to improve the computation efficiency. We prove that our procedure has the oracle properties. Both simulation studies and a real data example are carried out to examine finite sample performance of the proposed fixed and random effects selection procedure. Supplementary materials including R code used in this article and proofs for the theorems are available online.
Original languageEnglish
Pages (from-to)341-355
Number of pages15
JournalJournal of Computational and Graphical Statistics
Volume22
Issue number2
DOIs
Publication statusPublished - 17 Dec 2013
Externally publishedYes

Keywords

  • BIC
  • LASSO
  • Mixed-effects models

ASJC Scopus subject areas

  • Discrete Mathematics and Combinatorics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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