Missing data in regression models for non-commensurate multiple outcomes

REVSTAT-Statistical Journal

Volumn 9, Issue 1, 2011, Pages 37-55

  Teixeira Pinto, Armando ^a   Normand, Sharon Lise ^b  

^a University of Porto   (Portugal)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Direct maximization; Latent variable; Maximum likelihood; Missing data; Mixed outcomes; Multivariate; Non commensurate; Weighted generalized estimating equations

Indexed keywords

EID: 79955400516     PISSN: 16456726     EISSN: 21830371     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. Brooks, R. and the EuroQol Group (1996). EuroQol: the current state of play, Health Policy, 37, 53-72.
2. Cox, D.R. and Wermuth, N. (1992). Response models for binary and quantitative variables, Biometrika, 79, 441-461.
3. Dempster, A.; Laird, N. and Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm, Journal of Royal Statistical Society, Series B, 39, 1-38.
4. Dickey, B.; Normand, S.-L.T.; Hermann, R.C.; Eisen, S.V.; Cortes, D.E.; Cleary, P.D. and Ware, N. (2003). Guideline recommendations for treatment of schizophrenia: the impact of managed care, Arch. Gen. Psychiatry, 60, 340-8.
5. Dunson, D.B. (2000). Bayesian latent variable models for clustered mixed outcomes, Journal of the Royal Statistical Society, Series B: Statistical Methodology, 62, 355-366.
6. Fitzmaurice, G.M. and Laird, N.M. (1995). Regression models for a bivariate discrete and continuous outcome with clustering, Journal of the American Statistical Association, 90, 845-852.
7. Fitzmaurice, G.M. and Laird, N.M. (1997). Regression models for mixed discrete and continuous responses with potentially missing values, Biometrics, 53, 110-122.
8. Granja, C.; Teixeira-Pinto, A. and Costa-Pereira, A. (2002). Quality of life after intensive care: evaluation with EQ-5D questionnaire, Intensive Care Medicine, 28, 898-907.
9. Little, R.J. and Rubin, D. (2002). Statistical Analysis with Missing Data, John Wiley and Sons, Inc., Hoboken, New Jersey, U.S.A.
10. Olkin, I. and Tate, R. (1961). Multivariate correlation models with mixed discrete and continuous variables, The Annals of Mathematical Statistics, 32, 448-465.
11. Prentice, R.L. and Zhao, L.P. (1991). Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses, Biometrics, 47, 825-839.
12. Regan, M.M. and Catalano, P.J. (1999). Likelihood models for clustered binary and continuous outcomes: application to developmental toxicology, Biometrics, 55, 760-768.
13. Robins, J.; Rotnitzky, A. and Zhao, L. (1995). Analysis of semiparametric regression models for repeated outcomes in the presence of missing data, Journal of the American Statistical Association, 90, 106-121.
14. Sammel, M.D.; Ryan, L.M. and Legler, J.M. (1997). Latent variable models for mixed discrete and continuous outcomes, Journal of the Royal Statistical Society, Series B: Methodological, 59, 667-678.
15. Schafer, J. (1997). Analysis of Incomplete Multivariate Data (Chapter 9), Chapman and Hall /CRC Monographs on Statistics and Applied Probability, 72, New York, NY.
16. Schelling, G.; Stoll, C.; Haller, M.; Briegel, J.; Manert, W.; Hummel, T.; Lenhart, A.; Heyduck, M.; Polasek, J.; Meier, M.; Preuss, U.; Bullinger, M.; Schffel, W. and Peter, K. (1998). Health-related quality of life and posttraumatic stress disorder in survivors of the acute respiratory distress syndrome, Critical Care Medicine, 26, 634-635.
17. Shi, J. and Lee, S. (2000). Latent variable models with mixed continuous and polytomous data, Journal of the Royal Statistical Association, Series B, 62, 77-87.
18. Sukantarat, K.; Greer, S.; Brett, S. and Williamson, R. (2007). Physical and psychological sequelae of critical illness, British Journal of Health Psychology, 12, 65-74.
19. Teixeira-Pinto, A. and Normand, S.-L.T. (2009). Correlated bivariate continuous and binary outcomes: issues and applications, Statistics in Medicine, 28, 1753-73.
20. Zhao, L.P.; Prentice, R.L. and Self, S.G. (1992). Multivariate mean parameter estimation by using a partly exponential model, Journal of the Royal Statistical Society, Series B, 54, 805-811.