A mixture model for longitudinal data with application to assessment of noncompliance

Biometrics

Volumn 56, Issue 2, 2000, Pages 464-472

  Pauler, Donna K ^a   Laird, Nan M ^b  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Change point models; Compliance; Longitudinal data; Mixture model; Reversible jump Markov chain Monte Carlo

Indexed keywords

HIERARCHICAL SYSTEMS; MEDICAL APPLICATIONS; PATIENT TREATMENT; POPULATION STATISTICS; PROBABILITY DISTRIBUTIONS;

CHANGE-POINT MODELS; CLINICAL TRIAL; COMPLIANCE; FINITE MIXTURES; HIERARCHICAL MODEL; LONGITUDINAL DATA; MEMBERSHIP PROBABILITY; MIXTURE MODELING; REPEATED MEASURES; REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO;

MARKOV PROCESSES;

CD4 ANTIGEN; ZIDOVUDINE;

ARTICLE; CLINICAL TRIAL; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MEAN CORPUSCULAR VOLUME; MODEL; PATIENT COMPLIANCE; PROBABILITY; SYSTEM ANALYSIS;

EID: 0033933313     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2000.00464.x     Document Type: Article

References (16)

1. Brooks, S. P. and Giudici, P. (1998). Convergence assessment for reversible jump MCMC simulations. In Bayesian Statistics, Volume 6. Oxford: Oxford University Press.
2. Cowles, M. K., Carlin, B. P., and Connett, J. E. (1996). Bayesian tobit modeling of longitudinal ordinal clinical trial compliance data with nonignorable missingness. Journal of the American Statistical Association 91, 86-98.
3. Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Recognition and Machine Intelligence 6, 721-741.
4. Green, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711-732.
5. Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57, 97-109.
6. Kim, H. M. and Lagakos, S. W. (1994). Assessing drug compliance using longitudinal marker data, with application to AIDS. Statistics in Medicine 13, 2141-2153.
7. Lim, L. L. Y. (1992). Estimating compliance to study medication from serum drug levels: Application to an AIDS clinical trial of zidovudine. Biometrics 48, 619-630.
8. Lindsay, B. G. (1983). The geometry of mixture likelihoods: A general theory. Annals of Statistics 11, 86-94.
9. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E. (1953). Equations of state calculations by fast computing machine. Journal of Chemistry in Physics 21, 1087-1091.
10. Richardson, S. and Green, P. J. (1997). On Bayesian analysis of mixtures with an unknown number of components (disk: p. 758-792). Journal of the Royal Statistical Society, Series B 59, 731-758.
11. Roeder, K. and Wasserman, L. (1997). Practical Bayesian density estimation using mixtures of normals. Journal of the American Statistical Association 92, 894-902.
12. Rubin, D. B. (1984). Bayesianly justifiable and relevant frequency calculations for the applied statistician. The Annals of Statistics 12, 1151-1172.
13. Slate, E. H. and Cronin, K. A. (1997). Changepoint modeling of longitudinal PSA as a biomarker for prostate cancer. In Case Studies in Bayesian Statistics, Volume III, Gatsonis, Hodges, Kass, and Singpurwalla (eds), 435-456. New York: Springer-Verlag.
14. Titterington, D. M., Smith, A. F. M., and Makov, U. E. (1985). Statistical Analysis of Finite Mixture Distributions. Chichester, U.K.: John Wiley and Sons.
15. Volberding, P. A., Lagakos, S. W., Koch, M. A., et al. (1990). Zidovudine in asymptomatic human immunodeficiency virus infection: A controlled trial in persons with fewer than 500 CD4-positive cells per cubic millimeter. New England Journal of Medicine 322, 941-949.
16. Wang, W., Hsuan, F., and Chow, S. C. (1996). The impact of patient compliance on drug concentration profile in multiple doses. Statistics in Medicine 15, 659-669.