An evaluation of ridge estimator in linear mixed models: an example from kidney failure data

Ozkale M. R. , CAN F.

JOURNAL OF APPLIED STATISTICS, cilt.44, sa.12, ss.2251-2269, 2017 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 44 Konu: 12
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1080/02664763.2016.1252732
  • Sayfa Sayıları: ss.2251-2269


This paper is concerned with the ridge estimation of fixed and random effects in the context of Henderson's mixed model equations in the linear mixed model. For this purpose, a penalized likelihood method is proposed. A linear combination of ridge estimator for fixed and random effects is compared to a linear combination of best linear unbiased estimator for fixed and random effects under the mean-square error (MSE) matrix criterion. Additionally, for choosing the biasing parameter, a method of MSE under the ridge estimator is given. A real data analysis is provided to illustrate the theoretical results and a simulation study is conducted to characterize the performance of ridge and best linear unbiased estimators approach in the linear mixed model.