Biomedical Engineering Reference
In-Depth Information
Kalbfleisch, J. D. and Prentice, R. L. (2002).
The Statistical Analysis of Failure
Time Data, volume 360. New York: Wiley-Interscience.
Kay, R., Wu, J., and Wittes, J. (2011). On assessing the presence of evaluation-time
bias in progression-free survival in randomized trials.
Pharmaceutical Statistics
10, 213{217.
Lindsey, J. C. and Ryan, L. M. (1998). Methods for interval-censored data. Statistics
in Medicine 17, 219{238.
Middleton, M. R., Grob, J. J., Aaronson, N., Fierlbeck, G., Tilgen, W., Seiter, S.,
Gore, M., Aamdal, S., Cebon, J., Coates, A., et al. (2000). Randomized phase
III study of temozolomide versus dacarbazine in the treatment of patients with
advanced metastatic malignant melanoma. Journal of Clinical Oncology 18, 158{
166.
Panageas, K., Ben-Porat, L., Dickler, M. N., Chapman, P. B., and Schrag, D. (2007).
When you look matters: The effect of assessment schedule on progression-free
survival. JNCI Journal of the National Cancer Institute 99, 428{432.
So, Y., Johnston, G., and Kim, S. H. (2010). Analyzing Interval-Censored Survival
Data with SAS Software.
http://support.sas.com/kb/24/980.html
.
Sun, J. (2006). The Statistical Analysis of Interval-Censored Failure Time Data.
New York: Springer-Verlag.
Sun, J., Zhao, Q., and Zhao, X. (2005). Generalized logrank tests for interval-
censored failure time data. Scandinavian Journal of Statistics 32, 49{57.
Sun, X. and Chen, C. (2010). Comparison of Finkelstein's method with the conven-
tional approach for interval-censored data analysis. Statistics in Biopharmaceuti-
cal Research 2, 97{108.
Tuma, R. (2009). Progression-free survival remains debatable endpoint in cancer
trials. Journal of the National Cancer Institute 101, 1439{1441.
Zhang, M. and Davidian, M. (2008). \Smooth" semiparametric regression analysis
for arbitrarily censored time-to-event data. Biometrics 64, 567{576.
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