PRESS model selection in repeated measures data

Computational Statistics and Data Analysis

Volumn 30, Issue 2, 1999, Pages 169-184

  Liu, Honghu ^a   Weiss, Robert E ^b   Jennrich, Robert I ^a   Wenger, Neil S ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Correlated errors; Cross validation; Linear mixed effects model; Pivoting; Predicted residual sum of squares

Indexed keywords

DATA PROCESSING; MODELING;

COMPUTATIONAL METHODS; CORRELATION METHODS; ERROR ANALYSIS; MATHEMATICAL MODELS; REGRESSION ANALYSIS;

CORRELATED ERRORS; LINEAR MIXED EFFECTS MODEL; MULTIVARIATE LINEAR MODELS; PREDICTED RESIDUAL SUM OF SQUARES (PRESS);

DATA REDUCTION;

EID: 0033611824     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(98)00088-7     Document Type: Article

References (29)

1. Akaike, H., 1973. Information theory and an extension of the maximum likelihood principle. 2nd International Symposium on Information Theory, pp. 267-281.
2. Allen, D.M., 1971. The prediction sum of squares as a criterion for selecting predictor variables. University of Kentucky, Department of Statistics Technical Report # 23.
3. Allen D.M. The relationship between variable selection and data augmentation and a method for prediction. Technometrics. 16:1974;125-127.
4. BMDP Statistical Software Manual, 1992. BMDP Statistical Software Inc., University of California Press, Berkeley.
5. Diggle, P.J., Liang, K.Y., Zeger, S.L., 1994. The Analysis of Longitudinal Data. Oxford University Press, Oxford.
6. Draper, N.R., Smith, H., 1981. Applied Regression Analysis. Wiley, New York.
7. Garside M.J. The best subset in multiple regression analysis. J. Roy. Statist. Soc. C. 14:1965;196-200.
8. Geary D.N. Modeling the covariance structure of repeated measurements. Biometrics. 45:1989;1183-1195.
9. Geisser S. The predictive sample reuse method with applications. J. Amer. Statist. Assoc. 70:1975;320-328.
10. Geisser S., Eddy W.F. A predictive approach to model selection. J. Amer. Statist. Assoc. 74:1979;153-160.
11. Harville D.A. Maximum likelihood approaches to variance component estimation and related problems. J. Amer. Statist. Assoc. 72:1977;320-340.
12. Hocking, R.R., 1972. Criteria for selection of a subset regression: which one should be used? Technometrics 14, 967-970.
13. Jennrich R.I., Schluchter M.D. Unbalanced repeated-measures models with structured covariance matrices. Biometrics. 42:1986;805-820.
14. Kennedy, W.J., Gentle, J.E., 1980. Statistical Computing. Marcell Dekker, New York.
15. Laird N.M., Ware J.H. Random-effects models for longitudinal data. Biometrics. 38:1982;963-974.
16. Linhart, H., Zucchini, W., 1986. Model Selection. Wiley, New York.
17. Lisski P.L., Nummi T. Prediction in repeated measures models with engineering applications. Technometrics. 38:1996;25-36.
18. P Technometrics. 15:1973;661-675.
19. Murphy, D.J., Cluff, L.E. (Eds.), 1990. SUPPORT: Study to understand prognoses and preferences for outcomes and risks of treatment study design. J. Clin. Epidemiol. 43(s).
20. Pauler D.K. The Schwarz criterion and related methods for normal linear models. Biometrika. 85:1998;13-27.
21. Rice J.A., Silverman B.W. Estimating the mean and covariance structure nonparametrically when the data are curves. J. Roy. Statist. Soc. Ser. B. 53:1991;233-243.
22. SAS / IML Software, 1990. Usage and Reference. Version 6, SAS Institution Inc., Cary, North Carolina.
23. SAS Guide to Macro Processing, 1990. Version 6, second Ed. SAS Institute Inc., Cary, North Carolina.
24. Schwarz G. Estimating the dimension of a model. Ann. Statist. 6:1978;461-464.
25. Shao J. Linear model selection by cross-validation. J. Amer. Statist. Assoc. 88:1993;486-494.
26. Stone M. Cross-validatory choice and assessment of statistical predictions. J. Roy. Statist. Soc. Ser. B. 36:1974;111-147.
27. Vonesh E.F., Chinchilli V.M., Pu K. Goodness of fit in generalized non-linear mixed-effects models. Biometrics. 52:1996;572-587.
28. Weiss R.E., Lazaro C.G. Residual plots for repeated measures. Statist. Med. 11:1992;115-124.
29. Wolfinger R. Covariance structure selection in general mixed models. Commun. Statist. Simulation Comput. 22:1993;1079-1106.