JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Simulation Study on Model Selection Based on AIC under Unbalanced Design in Linear Mixed Effect Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Simulation Study on Model Selection Based on AIC under Unbalanced Design in Linear Mixed Effect Models
Lee, Yong-Hee;
  PDF(new window)
 Abstract
This article consider a performance model selection based on AIC under unbalanced deign in linear mixed effect models. Vaida and Balanchard (2005) proposed conditional AIC for model selection in linear mixed effect models when the prediction of random effects is of primary interest. Theoretical properties of cAIC and related criteria have been investigated by Liang et al. (2008) and Greven and Kneib (2010). However, all of the simulation studies were performed under a balanced design. Even though functional form of AIC remain same even under the unbalanced deign, it is worthwhile to investigate performance of AIC based model selection criteria under the unbalanced design. The simulation study in this article shows how unbalancedness affects model selection in linear mixed effect models.
 Keywords
Linear mixed effect models;unbalanced design;AIC;model selection;
 Language
Korean
 Cited by
1.
실내 항온과 온실 변온조건에서 목화진딧물의 온도 발육비교,김도익;고숙주;최덕수;강범용;박창규;김선곤;박종대;김상수;

한국응용곤충학회지, 2012. vol.51. 4, pp.421-429 crossref(new window)
2.
항온과 변온조건에서 복숭아혹진딧물의 발육비교 및 온도 발육모형,김도익;최덕수;고숙주;강범용;박창규;김선곤;박종대;김상수;

한국응용곤충학회지, 2012. vol.51. 4, pp.431-438 crossref(new window)
1.
Comparison of Development times of Myzus persicae (Hemiptera:Aphididae) between the Constant and Variable Temperatures and its Temperature-dependent Development Models, Korean journal of applied entomology, 2012, 51, 4, 431  crossref(new windwow)
2.
Comparison of Temperature-dependent Development Model of Aphis gossypii (Hemiptera: Aphididae) under Constant Temperature and Fluctuating Temperature, Korean journal of applied entomology, 2012, 51, 4, 421  crossref(new windwow)
 References
1.
Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle, Second International Symposium on Information Theory, 267–281, Akademiai Kiado, Budapest.

2.
Greven, S. and Kneib, T. (2010). On the behavior of marginal and conditional AIC in linear mixed models, Biometrika, 97, 773–789.

3.
Hartley, H. O. and Rao, J. N. K. (1967). Maximum-likelihood estimation for the mixed analysis of variance model, Biometrika, 54, 93–108.

4.
Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems, Journal of the American Statistical Association, 72, 320–338.

5.
Jiang, J. (2009). Linear and Generalized Linear Mixed Models and Their Applications, Springer, New York.

6.
Khuri, A. I., Mathew, T. and Sinha, B. K. (1998). Statistical Tests in Mixed linear Models, John Wiley & Sons.

7.
Liang, H., Wu, H. and Zou, G. (2008). A note on conditional AIC for linear mixed-effects models, Biometrika, 95, 773–778.

8.
Searle, S. R., Casella, G. and McCulloch, C. E. (1992). Variance Components, John Wiley & Sons.

9.
Vaida, F. and Blanchard, S. (2005). Conditional Akaike information for mixed-effects models, Biometrika, 92, 351–370.