BibTex RIS Kaynak Göster

ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY

Yıl 2013, Cilt: 2 Sayı: 2, 91 - 102, 06.05.2015

Öz

Smoothing methods that use basis functions with penalization can be formulated as fits in formlinear mixed effects models. This allows s uch models to be fitted using sta ndard mixed models structures. In this paper we provide an estimation and inference for linear mixed models using restrict- ed maximum likelihood and penalized spline smoothing, and describe the connection between the two. To this end, a real data example is considered and model is fitted in R using diff erent package. We see that penalized spline smoothing expressed in form of linear mixed model gives the better results than standard mixed effects model.

Kaynakça

  • Coull, B. A., Ruppert, D. and Wand, M.P. (2001). Simple Incorporation of Interactions into Additive Models. Biometrics 57, 539–545.
  • Coull, B.A. , Schwartz, J. and Wand, M.P. (2001). Respiratory Health and Air Pollution: Additive Mixed Model Analysis. Biostatistics 2 , 337–349.
  • Davidian, M and Giltinan, D.M. (1996). Nonlinear Models for Repeated Measurement Data, Chapman and Hall, London.
  • Diggle, P., Heagerty, P., Liang, K.-L., and Zeger, S. (2002). Analysis of Longitudinal Data. 2nd ed, Oxford University Press.
  • Eilers, P.H.C and Marx, B.D. (1996). Flexible Smoothing with B-Splines and Penalties.Statistical Science. 11.
  • Green P. J. and Silverman, B. W. (1994). Nonparametric Regression and Generalized Linear Model, Chapman &Hall, London
  • McCulloch, C.E and Searle, S.R. (2001). Generalized, Linear, and Mixed Models. Willey, New York.
  • O’Sullivan, F. (1986). A Statistical Perspective on Ill-Posed Inverse Problems (C/R: P519-527). Statistical Science 1 , 502–518.
  • Parise, H., Wand, M.P. , Ruppert, D. and Ryan, L. (2001). Incorporation of Historical Controls using Semiparametric Mixed Models. Journal of the Royal Statistical Society: Series C Applied Statistics, 50, 31–42.
  • Pinheiro, J.C. and Bates, D.M. (2000). Mixed Effects Models in S and S-Plus, Springer-Verlag, New York.
  • Ruppert, D., Wand, M. and Carroll, R. (2003). Semiparametric Regression, Cambridge University Press, Cambridge.
  • Shively, T. S., Kohn, R. And Wood, S. (1999). Variable Selection and Function Estimation in Additive Nonparametric Regression using A Data-Based Prior (with discussion). Journal of the American Statistical Association, 94, 777–806.

DOĞRUSAL KARMA ETKİLİ MODELLERDE TAHMİN VE ÇIKARSAMALAR: BİR KARŞILAŞTIRMALI ÇALIŞMA

Yıl 2013, Cilt: 2 Sayı: 2, 91 - 102, 06.05.2015

Öz

Kaynakça

  • Coull, B. A., Ruppert, D. and Wand, M.P. (2001). Simple Incorporation of Interactions into Additive Models. Biometrics 57, 539–545.
  • Coull, B.A. , Schwartz, J. and Wand, M.P. (2001). Respiratory Health and Air Pollution: Additive Mixed Model Analysis. Biostatistics 2 , 337–349.
  • Davidian, M and Giltinan, D.M. (1996). Nonlinear Models for Repeated Measurement Data, Chapman and Hall, London.
  • Diggle, P., Heagerty, P., Liang, K.-L., and Zeger, S. (2002). Analysis of Longitudinal Data. 2nd ed, Oxford University Press.
  • Eilers, P.H.C and Marx, B.D. (1996). Flexible Smoothing with B-Splines and Penalties.Statistical Science. 11.
  • Green P. J. and Silverman, B. W. (1994). Nonparametric Regression and Generalized Linear Model, Chapman &Hall, London
  • McCulloch, C.E and Searle, S.R. (2001). Generalized, Linear, and Mixed Models. Willey, New York.
  • O’Sullivan, F. (1986). A Statistical Perspective on Ill-Posed Inverse Problems (C/R: P519-527). Statistical Science 1 , 502–518.
  • Parise, H., Wand, M.P. , Ruppert, D. and Ryan, L. (2001). Incorporation of Historical Controls using Semiparametric Mixed Models. Journal of the Royal Statistical Society: Series C Applied Statistics, 50, 31–42.
  • Pinheiro, J.C. and Bates, D.M. (2000). Mixed Effects Models in S and S-Plus, Springer-Verlag, New York.
  • Ruppert, D., Wand, M. and Carroll, R. (2003). Semiparametric Regression, Cambridge University Press, Cambridge.
  • Shively, T. S., Kohn, R. And Wood, S. (1999). Variable Selection and Function Estimation in Additive Nonparametric Regression using A Data-Based Prior (with discussion). Journal of the American Statistical Association, 94, 777–806.
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Yazarlar

Özlem Aksoy

Dursun Aydın

Yayımlanma Tarihi 6 Mayıs 2015
Yayımlandığı Sayı Yıl 2013 Cilt: 2 Sayı: 2

Kaynak Göster

APA Aksoy, Ö., & Aydın, D. (2015). ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY. Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi - B Teorik Bilimler, 2(2), 91-102.
AMA Aksoy Ö, Aydın D. ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY. AUBTD-B. Mayıs 2015;2(2):91-102.
Chicago Aksoy, Özlem, ve Dursun Aydın. “ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY”. Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi - B Teorik Bilimler 2, sy. 2 (Mayıs 2015): 91-102.
EndNote Aksoy Ö, Aydın D (01 Mayıs 2015) ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY. Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi - B Teorik Bilimler 2 2 91–102.
IEEE Ö. Aksoy ve D. Aydın, “ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY”, AUBTD-B, c. 2, sy. 2, ss. 91–102, 2015.
ISNAD Aksoy, Özlem - Aydın, Dursun. “ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY”. Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi - B Teorik Bilimler 2/2 (Mayıs2015), 91-102.
JAMA Aksoy Ö, Aydın D. ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY. AUBTD-B. 2015;2:91–102.
MLA Aksoy, Özlem ve Dursun Aydın. “ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY”. Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi - B Teorik Bilimler, c. 2, sy. 2, 2015, ss. 91-102.
Vancouver Aksoy Ö, Aydın D. ESTIMATION AND INFERENCES IN LINEAR MIXED EFFECTS MODELS: A COMPARATIVE STUDY. AUBTD-B. 2015;2(2):91-102.