Estimation of covariate effects in generalized linear mixed models with a misspecified distribution ofrandom intercepts and slopes

Statistics in Medicine

Volumn 32, Issue 14, 2013, Pages 2419-2429

  Neuhaus, John M ^a   Mcculloch, Charles E ^a   Boylan, Ross ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Generalized linear mixed models; Kullback Leibler divergence; Misspecified mixing distributions

Indexed keywords

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; CONFIDENCE INTERVAL; EFFECT SIZE; GENERALIZED LINEAR MIXED MODEL; LONGITUDINAL STUDY; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; POISSON DISTRIBUTION; PREDICTOR VARIABLE; RANDOM INTERCEPT; RANDOM SLOPE; SIMULATION;

ANALYSIS OF VARIANCE; BIAS (EPIDEMIOLOGY); BIOSTATISTICS; CLUSTER ANALYSIS; CONFIDENCE INTERVALS; DATA INTERPRETATION, STATISTICAL; HUMANS; LIKELIHOOD FUNCTIONS; LINEAR MODELS; LONGITUDINAL STUDIES;

EID: 84878648473     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.5682     Document Type: Article

References (16)

1. McCulloch CE, Searle SR, Neuhaus JM. Generalized, Linear and Mixed Models, Second edition. Wiley: New York, 2008.
2. Bent S, Kane C, Shinohara K, Neuhaus J, Hudes E, Goldberg H, Avins A. A randomized controlled trial of saw palmetto for benign prostatic hyperplasia. New England Journal of Medicine 2006; 354:557-566.
3. Neuhaus JM, Hauck WW, Kalbfleisch JD. The effects of mixture distribution misspecification when fitting mixed-effects logistic models. Biometrika 1992; 79:755-762.
4. Neuhaus JM, Kalbfleisch JD, Hauck WW. Conditions for consistent estimation in mixed-effects models for binary matched-pairs data. The Canadian Journal of Statistics 1994; 22:139-148.
5. Butler SM, Louis TA. Random effects models with non-parametric priors (Disc: p2017-2023). Statistics in Medicine 1992; 11:1981-2000.
6. 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; 23:541-556.
7. Heagerty PJ, Kurland BF. Misspecified maximum likelihood estimates and generalised linear mixed models. Biometrika 2001; 88:973-986.
8. Neuhaus JM, McCulloch CE. Separating between- and within-cluster covariate effects using conditional and partitioning methods. Journal of the Royal Statistical Society, Series B 2006; 68:859-872.
9. McCulloch CE, Neuhaus JM. Misspecifying the shape of a random effects distribution: why getting it wrong may not matter. Statistical Science 2011; 26:388-402.
10. Litière S, Alonso A, Molenberghs G. 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 2008; 27:3125-3144.
11. Zhang P, Song PXK, Qu A, Greene T. Efficient estimation for patient-specific rates of disease progression using nonnormal linear mixed models. Biometrics 2008; 64:29-38.
12. Neuhaus JM, McCulloch CE. Estimation of covariate effects in generalized linear mixed models with informative cluster sizes. Biometrika 2011; 98:147-162.
13. Akaike H. Information theory and an extension of the maximum likelihood principle. In Second International Symposium on Information Theory, Petrov BN, Czáki F (eds). Akademiai Kiadó: Budapest, 1973; 267-281.
14. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982; 50:1-25.
15. Kullback S. Information Theory and Statistics. John Wiley and Sons: New York, 1959.
16. McCullagh P, Nelder J. Generalized Linear Models. Chapman and Hall: London, 1989.