The impact of a misspecified random-effects distribution on the estimation and the performance of inferential procedures in generalized linear mixed models

Statistics in Medicine

Volumn 27, Issue 16, 2008, Pages 3125-3144

  Litière, Saskia ^a   Alonso, A ^a   Molenberghs, G ^a  

^a HASSELT UNIVERSITY   (Belgium)

Author keywords

Consistency; Heterogeneity model; Kullback Leibler information criterion; Non normal random effects; Power; Type I error

Indexed keywords

NEUROLEPTIC AGENT; RISPERIDONE;

ARTICLE; CLINICAL TRIAL; COMPUTER SIMULATION; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DRUG EFFICACY; HUMAN; INTERNAL CONSISTENCY; MAJOR CLINICAL STUDY; MATHEMATICAL COMPUTING; MAXIMUM LIKELIHOOD METHOD; RANDOMIZATION; RANDOMIZED CONTROLLED TRIAL; SAMPLING ERROR; SCHIZOPHRENIA; SENSITIVITY ANALYSIS; STATISTICAL MODEL; TREATMENT OUTCOME; TREATMENT RESPONSE;

ANTIPSYCHOTIC AGENTS; COMPUTER SIMULATION; HUMANS; LIKELIHOOD FUNCTIONS; LINEAR MODELS; RANDOM ALLOCATION; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SCHIZOPHRENIA;

EID: 42749091873     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3157     Document Type: Article

References (25)

1. Diggle PJ, Heagerty P, Liang K-Y, Zeger SL. Analysis of Longitudinal Data. Oxford University Press: New York, 2002.
2. Molenberghs G, Verbeke G. Models for Discrete Longitudinal Data. Springer: New York, 2005.
3. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982; 38:963-974.
4. Verbeke G, Molenberghs G. Linear Mixed Models for Longitudinal Data. Springer: New York, 2000.
5. Verbeke G, Lesaffre E. The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data. Computational Statistics and Data Analysis 1997; 53:541-556.
6. Neuhaus JM, Hauck WW, Kalbfleisch JD. The effects of mixture distribution misspecification when fitting mixed-effects logistic models. Biometrika 1992; 79:755-762.
7. Chen J, Zhang D, Davidian M. A Monte Carlo EM algorithm for generalized linear mixed models with flexible random-effects distribution. Biostatistics 2002; 3:347-360.
8. Agresti A, Caffo, B, Ohman-Strickland P. Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies. Computational Statistics and Data Analysis 2004; 47(3):639-653.
9. Heagerty PJ, Kurland BF. Misspecified maximum likelihood estimates and generalised linear mixed models. Biometrika 2001; 88:973-985.
10. Aitkin M. A general maximum likelihood analysis of variance components in generalized linear models. Biometrics 1999; 55:117-128.
11. Aitkin M. Meta-analysis by random effect modelling in generalised linear models. Statistics in Medicine 1999; 18:2343-2351.
12. Burr D, Doss H, Cooke GE, Goldschmidt-Clermont PJ. A meta-analysis of studies on the association of the platelet P1A polymorphism of glycoprotein IIIa and risk of coronary heart disease. Statistics in Medicine 2003; 22:1741-1760.
13. Burr D, Doss H. A Bayesian semi-parametric model for random effects meta-analysis. Journal of American Statistical Association 2005; 100:242-251.
14. Ohlssen DI, Sharples LD, Spiegelhalter DJ. Flexible random-effects models using Bayesian semi-parametric models: applications in institutional comparisons. Statistics in Medicine 2007; 26:2088-2112.
15. Lee KJ, Thompson SG. Flexible parametric models for random effects distributions. Statistics in Medicine 2007; DOI: 10.1002/ sim.2897.
16. Marshall EC, Spiegelhalter DJ. Comparing institutional performance using Markov chain Monte Carlo methods. In Statistical Analysis of Medical Data: New Developments, Everitt BS, Dunn G (eds). Arnold: London, 1998; 229-249.
17. Arends LR, Hoes AW, Lubsen J, Deiderik EG, Stijnen T. Baseline risk as a predictor of treatment benefit: three clinical meta-reanalysis. Statistics in Medicine 2000; 19:3497-3518.
18. Fieuws S, Spiessens B, Draney K. Mixture models. In Explanatory Item Response Models: A Generalized Linear and Nonlinear Approach, De Boeck P, Wilson M (eds). Springer: New York, 2004: 317-340.
19. Alonso A, Geys H, Molenberghs G, Kenward MG, Vangeneugden T. Validation of surrogate markers in multiple randomized clinical trials with repeated measurements: canonical correlation approach. Biometrics 2004; 60(4):845-853.
20. Rubin DB. Inference and missing data. Biometrika 1976; 63:581-592.
21. Kenward MG, Molenberghs G. Missing Data in Clinical Studies. Wiley: Chichester, 2007.
22. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982; 50:1-25.
23. Böhning D. Computer-assisted Analysis of Mixtures and Applications: Meta-analysis, Disease Mapping and Others. Monographs on Statistics and Applied Probability, vol. 81. Chapman & Hall/CRC Press: London, Boca Raton, FL, 1999.
24. Nelson KP, Lipsitz SR, Fitzmaurice GM, Ibrahim J, Parzen M, Strawderman R. Use of the probability integral transformation to fit nonlinear mixed-effects models with normormal random effects. Journal of Computational and Graphical Statistics 2006; 15(1):39-57.
25. Lee Y, Nelder JA. Hierarchical generalized linear models (with discussion). Journal of the Royal Statistical Society, Series B 1996; 58:619-678.