Mixed effects models with bivariate and univariate association parameters for longitudinal bivariate binary response data

Biometrics

Volumn 55, Issue 1, 1999, Pages 85-93

  Ten Have, Thomas R ^a   Morabia, Alfredo ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b GENEVA UNIVERSITY HOSPITALS   (Switzerland)

Author keywords

Binomial mixtures; Marginal models; Multivariate logistic models

Indexed keywords

RANDOM PROCESSES;

ACROSS TIME; BINARY RESPONSE; BINOMIAL MIXTURE; BIVARIATE; LOGISTICS MODEL; MARGINAL MODELS; MULTIVARIATE LOGISTIC MODEL; ODD RATIOS; RANDOM EFFECTS; UNIVARIATE;

RISK ASSESSMENT;

ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; HUMAN; HYPERCHOLESTEROLEMIA; HYPERTENSION; INTERMETHOD COMPARISON; PREDICTION; RELIABILITY; SIMULATION; STATISTICAL MODEL; VALIDATION PROCESS; VARIANCE;

EID: 0032929195     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.1999.00085.x     Document Type: Article

References (20)

1. Becker, M. P. and Balagtas, C. C. (1993). Marginal modeling for binary cross-over data. Biometrics 49, 997-1009.
2. Carey, V., Zeger, S. L., and Diggle, P. (1993). Modelling multivariate binary data with alternating logistic regressions. Biometrika 80, 517-526.
3. Dale, J. R. (1986). Global cross-ratio models for bivariate discrete ordered responses. Biometrics 42, 909-917.
4. De Gruttola, V. and Ming Tu, X. (1994). Modelling progression of CD4-lymphocyte count and its relationship to survival time. Biometrics 50, 1003-1014.
5. Fitzmaurice, G. M., Molenberghs, G., and Lipsitz, S. R. (1995). Regression models for longitudinal binary responses with informative drop-outs. Journal of the Royal Statistical Society, Series B 57, 691-704.
6. JNC (Joint Committee on Detection, Evaluation, and Treatment of High Blood Pressure). (1993). The fifth report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure of the NIH/NHLBI (JNC V). Archives of Internal Medicine 153, 149-152.
7. Lang, J. B. and Agresti, A. (1994). Simultaneously modeling joint and marginal distributions of multivariate categorical responses. Journal of the American Statistical Association 89, 625-632.
8. Lefkopoulou, M., Rotnitzky, A., and Ryan, L. M. (1995). Trend tests for clustered data. In Statistics in Toxicology, B. T. Morgan (ed). London: Oxford University Press.
9. Legler, J. M. and Ryan, L. M. (1997). Latent variable models for teratogenesis using multiple binary outcomes. Journal of the American Statistical Association 92, 13-20.
10. Liang, K.-Y. and Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73, 13-22.
11. Little, R. J. A. (1995). Modeling the drop-out mechanism in repeated measures studies. Journal of the American Statistical Association 92, 13-20.
12. Massari, A., Point, C., Truffe, P., Chatellier, G., Simon, A., and Menard, J. (1995). Effect of 2 types of diet changes on dietary habits, body weight, and cholesterol levels in high risk cardiovascular patients. Archives des Maladies du Coeur et des Vaisseaux 88, 1101-1104.
13. McCullagh, P. and Neider, J. R. (1989). Generalized Linear Models, 2nd edition. London: Chapman and Hall.
14. Molenberghs, G. and Lesaffre, E. (1994). Marginal modeling of correlated ordinal data using a Plackett distribution. Journal of the American Statistical Association 89, 633-644.
15. NCEP (National Cholesterol Education Program). (1993). Summary of the second report of the NCEP expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel II). Journal of the American Medical Association 269, 3015-3023.
16. Neuhaus, J. M., Kalbfleisch, J. D., and Hauck, W. W. (1991). A comparison of cluster-specific and population-averaged approaches for analyzing correlated binary data. International Statistical Review 59, 25-35.
17. Rubin, D. B. (1976). Inference and missing data. Biometrika 63, 581-592.
18. SERC (Statistics and Epidemiology Research Corporation). (1990). EGRET Reference Manual. Seattle: Statistics and Epidemiology Research Corporation.
19. Stiratelli, R., Laird, N., and Ware, J. H. (1984). Random-effects models for serial observations with binary response. Biometrics 40, 961-971.
20. Zeger, S. L., Liang, K. Y., and Albert, P. A. (1988). Models for longitudinal data: A generalized estimating equation approach. Biometrics 44, 1049-1060.