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
Bölüm Araştırma Makalesi
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 (Mayıs 2015), 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.