http://www.isped.u-bordeaux.fr/
REFERENCES
Burzykowski, T., Molenberghs, G., & Buyse, M. (2004). The validation of surrogate end
points by using data from randomized clinical trials: a case-study in advanced colorectal
cancer. Journal of the Royal Statistical Society: Series A (Statistics in Society), 167(1),
103–124.
Burzykowski, T., Molenberghs, G., & Buyse, M. (2005). The evaluation of surrogate
endpoints (p. 408). New York: Springer.
Burzykowski, T., Molenberghs, G., Buyse, M., Geys, H., & Renard, D. (2001). Validation
of surrogate end points in multiple randomized clinical trials with failure time end points.
Applied Statistics, 50(4), 405–422. Blackwell Publishers.
Buyse, M., Burzykowski, T., Carroll, K., Michiels, S., Sargent, D. J., Miller, L. L., Elfring, G.
L., et al. (2007). Progression-free survival is a surrogate for survival in advanced
colorectal cancer. Journal of Clinical Oncology, 25(33), 5218–5224.
Cook, R. J., & Lawless, J. F. (2001). Some comments on e ciency gains from auxiliary
information for right-censored data, 96, 191–202.
Faucett, C. L., Schenker, N., & Taylor, J. M. G. (2002). Survival analysis using auxiliary
variables via multiple imputation, with application to AIDS clinical trial data. Biometrics,
58(1), 37–47.
Fleming, T. R., Prentice, R. L., Pepe, M. S., & Glidden, D. V. (1994). Surrogate and
auxiliary endpoints in clinical trials, with potential applications in cancer and aids
research. Statistics in medicine, 13(9), 955–968.
Hsu, C., & Taylor, J. M. G. (2009). Nonparametric comparison of two survival functions
with dependent censoring via nonparametric multiple imputation, (November 2008), 462–
475.
Huang, X., & Liu, L. (2007). A joint frailty model for survival and gap times between
recurrent events. Biometrics, 63(2), 389–397.
Kalbfleisch, J. D., Schaubel, D. E., Ye, Y., & Gong, Q. (2013). An Estimating Function
Approach to the Analysis of Recurrent and Terminal Events. Biometrics, 1–9.
Li, Y., Taylor, J. M. G., Elliott, M. R., & Sargent, D. J. (2011). Causal assessment of
surrogacy in a meta-analysis of colorectal cancer trials. Biostatistics (Oxford, England),
12(3), 478–92.
Mauguen, A., Rachet, B., Mathoulin-Pélissier, S., MacGrogan, G., Laurent, A., &
Rondeau, V. (2013). Dynamic prediction of risk of death using history of cancer
recurrences in joint frailty models. Statistics in medicine, 32(30), 5366–80.
Mazroui, Y., Mathoulin-Pélissier, S., Macgrogan, G., Brouste, V., & Rondeau, V. (2013).
Multivariate frailty models for two types of recurrent events with a dependent terminal
event : Application to breast cancer data. Biometrical Journal, 55(6), 886–884.
Prentice, R. L. (1989). surrogate endpoints in clinical trials: definition and operational
criteria. Statistics in medicine, 8, 431–440.
Proust, C., & Jacqmin-Gadda, H. (2005). Estimation of linear mixed models with a mixture
of distribution for the random effects. Computer methods and programs in biomedicine,
78(2), 165–73. doi:10.1016/j.cmpb.2004.12.004
Rondeau, V., & Gonzalez, J. R. (2005). frailtypack: A computer program for the analysis of
correlated failure time data using penalized likelihood estimation. Computer Methods and
Programs in Biomedicine, 80(2), 154–164. Elsevier.