Breslow, N. (1972). Contribution to the discussion of paper by D.R. Cox. Journal of the Royal Statistical Society, B, 34, 187-220.

Breslow, N. (1974). Covariance Analysis of Censored Survival Data. Biometrics, 30, 89-99.

Chen, H.Y. and Little, R.J.A (1999). Proportional Hazards Regression with Missing Covariates. Journal of the American Statistical Association, 94, 896-908.

Cox, D.R. (1972). Regression Models and Life Tables, with Discussion. Journal of the Royal Statistical Society, B, 34, 187-220.

Dafni, U.G. and Tsiatis, A.A. (1998). Evaluating Surrogate Markers of Clinical Outcome when measured with Error. Biometrics, 54, 1445-1462.

Diggle, P.J. and Kenward, M.G. (1994). Informative Dropout in Longitudinal Data Analysis (with discussion). Applied Statistics, 43, 49-93.

Dupuy, J.F and Mesbah, M. (2002). Joint Modeling of Event Time Data and Nonignorable Missing Longitudinal Data. Lifetime Data Analysis, 8,99115

Dupuy, J.-F.; Mesbah, M.(2004) Estimation of the asymptotic variance of SPML estimators in the Cox model with a missing time-dependent covariate. Communications in Statistics - Theory and Methods S3, .6, 1385-1401 (2004).

Dupuy, J.-F.; Grama, I. and Mesbah, M. (2003) Normalité asymptotique des estimateurs semi paramétriques dans le modèle de Cox avec covariable manquante non-ignorable (In french) C. R. Acad. Sci. Paris Sér. I Math. 336, No.l, 81-84.

Hogan, J.W., and Laird, N.M. (1997). Model Based Approaches to Analysing Incomplete Longitudinal and Failure Time Data. Statistics in Medicine, 16, 239-257.

Kalbfleisch, J.D. and Prentice, R.L. (1980). The Statistical Analysis of Failure Time Data. Wiley: New-York.

Lin, D.Y. (1991). Goodness-of-Fit Analysis for the Cox Regression Model Based on a Class of Parameter Estimators. Journal of the American Statistical Association, 86, 725-728.

Lin, D.Y. and Ying, Z. (1993). Cox Regression with Incomplete Covariate Measurements. Journal of the American Statistical Association, 88, 13411349.

Little, R.J.A. and Rubin, D.B. (1987). Statistical Analysis with Missing Data. Wiley: New-York.

Little, R.J.A. (1995). Modeling the Dropout Mechanism in Repeated Measure Studies. Journal of the American Statistical Association, 90, 1112-1121.

Martinussen, T. (1999). Cox Regression with Incomplete Covariate Measurements using the EM-algorithm. Scandinavian Journal of Statistics, 26, 479-491.

Molenberghs, G., Kenward, M.G. and Lesaffre, E. (1997). The Analysis of Longitudinal Ordinal Data with Nonrandom Dropout. Biometrika, 84, 33-44.

Paik, M.C. and Tsai, W.Y. (1997). On Using the Cox Proportional Hazards Model with Missing Covariates. Biometrika, 84, 579-593.

journal Tsiatis, A.A., DeGruttola, V. and Wulfsohn, M.S. (1995). Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS. Journal of the American Statistical Association, 90, 27-37.

Verbeke, G. and Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. Springer-Verlag: New-York.

Troxel, A.B., Lipsitz, S.R. and Harrington, D.P. (1998). Marginal Models for the Analysis of Longitudinal Measurements with Nonignorable Nonmonotone Missing Data. Biometrika, 85, 661-672.

Wang-Clow, F. Lange, M., Laird, N.M. and Ware, J.H. (1995). A Simulation Study of Estimators for Rate of Change in Longitudinal Studies with Attrition. Statistics in Medicine, 14, 283-297.

Wu, M.C. and Carroll (1988). Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process. Biometrics, 44, 175-188.

Wulfsohn, M.S. and Tsiatis, A.A. (1997). A Joint Model for Survival and Longitudinal Data Measured with error. Biometrics, 53, 330-339.

Was this article helpful?

0 0

Post a comment