A family of tests to detect misspecifications in the random-effects structure of generalized linear mixed models

Computational Statistics and Data Analysis

Volumn 52, Issue 9, 2008, Pages 4474-4486

  Alonso, A ^a   Litiere S ^a   Molenberghs, G ^a  

^a HASSELT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

COVARIANCE MATRIX; EIGENVALUES AND EIGENFUNCTIONS; MAXIMUM LIKELIHOOD ESTIMATION; PARAMETER ESTIMATION; PROBABILITY;

DIAGNOSTIC TOOLS; GENERALIZED LINEAR MIXED MODELS; MISSPECIFICATIONS; RANDOM-EFFECTS STRUCTURE;

LINEAR SYSTEMS;

EID: 42749096545     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2008.02.033     Document Type: Article

References (21)

1. Agresti A. Categorical Data Analysis (2002), Wiley, Hoboken, NJ
2. Agresti A., Caffo B., and Ohman-Strickland P. Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies. Comput. Statist. Data Anal. 47 (2004) 639-653
3. Alonso A., Geys H., Molenberghs G., Kenward M.G., and Vangeneugden T. Validation of surrogate markers in multiple randomized clinical trials with repeated measurements: Canonical correlation approach. Biometrics 60 (2004) 845-853
4. Anderson T.W. Asymptotic theory for principal component analysis. Ann. Math. Stat. 34 (1963) 122-148
5. Breslow N.E., and Clayton D.G. Approximate inference in generalized linear mixed models. J. Amer. Statist. Assoc. 88 (1993) 9-25
6. Chen J., Zhang D., and Davidian M. A Monte Carlo EM algorithm for generalized linear mixed models with flexible random-effects distribution. Biostatistics 3 (2002) 347-360
7. Diggle P.J., Heagerty P., Liang K.-Y., and Zeger S.L. Analysis of Longitudinal Data (2002), Oxford University Press, New York
8. Girschick M.S. On the sample theory of the roots of determinantal equations. Ann. Math. Stat. 10 (1939) 203-224
9. Heagerty P.J., and Kurland B.F. Misspecified maximum likelihood estimates and generalised linear mixed models. Biometrika 88 (2001) 973-985
10. Kenward M.G., and Molenberghs G. Missing Data in Clinical Studies (2007), Wiley, Chichester
11. Lesaffre E., and Spiessens B. On the effect of the number of quadrature points in a logistic random-effects model: An example. Appl. Stat. 50 (2001) 325-335
12. Lehmann E.L. Elements of Large Sample Theory (1999), Springer-Verlag, New York
13. Litière S., Alonso A., and Molenberghs G. Type I and type II error random-effects misspecification in generalized linear mixed models. Biometrics 63 (2007) 1038-1044
14. Litière S., Alonso A., and Molenberghs G. The impact of a misspecified random-effects distribution on the estimation and the performance of inferential procedures in generalized linear mixed models. Statist. Med. (2008) 10.1002/sim.3157
15. Molenberghs G., and Verbeke G. Models for Discrete Longitudinal Data (2005), Springer, New York
16. Neuhaus J.M., Hauck W.W., and Kalbfleisch J.D. The effects of mixture distribution misspecification when fitting mixed-effects logistic models. Biometrika 79 (1992) 755-762
17. Tchetgen E.J., and Coull B.A. A diagnostic test for the mixing distribution in a generalized linear mixed model. Biometrika 93 (2006) 1003-1010
18. Waagepetersen R. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models. Scand. J. Statist. 33 (2006) 721-731
19. Waternaux C.M. Asymptotic distribution of the sample roots for a nonnormal population. Biometrika 63 (1976) 639-645
20. White H. Maximum likelihood estimation of misspecified models. Econometrica 50 (1982) 1-25
21. Wolfinger R., and O'Connell M. Generalized linear mixed models: A pseudo-likelihood approach. J. Stat. Comput. Simul. 48 (1993) 233-243