| 參考文獻 |
[1] Akritas, M. G. (1994). “Nearest neighbor estimation of a bivariate distribution under
random censoring.” Annals of Statistics, 22, 1299-1327.
[2] Brown, E. R., Ibrahim, J. G. and DeGruttola, V. (2005). “A flexible B-spline model for
multiple longitudinal biomarkers and survival.” Biometrics, 61, 64-73..
[3] Ciampi, A. and Etezadi-Amoli, J. (1985). “A general model for testing the proportional
hazards and the accelerated failure time hypothesis in the analysis ofcensored survival
data with covariate.” Communications in Statistics, 14, 651-667.
[4] Cleveland, W. S. (1979). “Robust Locally Weighted Regression and Smoothing Scatterplots.”
Journal of the American Statistical Associtatio, 74, 829-836.
[5] Cox, D. R. (1972). “Regression Models and Life-Tables.” Journal of the RoyalStatistical
SocietySeries B (Methodological), 34, 187-220.
[6] Cox, D. R. and Oakes, D. (1984). Analysis of Survival Data, Chapman and Hall,London,
New York.
[7] knuth84 (Dafini, U. G. and Tsiatis, A. A). “1998.” Evaluating surrogate markers of
clinical outcome measured with error, Biometrics, 54.1445-1462
[8] Dempster, A. P., Laird,N. M. and Rubin, D. B. (1977). “Maximum Likelihood from
Imcomplete Data via the EM Algorithm.” Journal of the Royal StatisticalSociety Series
B (Methodological), 39, 1-38.
[9] Dimitris Rizopoulo (2010). “JM : An R Package for the Joint Modelling of Longitudinal
and Time-to-Event Data.” Journal of Statistical Software, 35, 9.
[10] Dubin, J. A., Muller, H. G. and Wang, J. L. (2001). “Event history graphs for censored
survival data.” Statistics in Medicin, 20, 2951-2964.
[11] Etezadi-Amoli J. and Campi A (1987). “Extended hazard regression for censored survival
data with covariates: A spline approximation for the baseline hazard function.” Bio-
metrics B, 43, 181-192.
[12] Goldman A, Carlin B, Crane L, Launer C, Korvick J, Deyton L, Abrams D (1996). “Response
of CD4+ and Clinical Consequences to Treatment Using ddI or ddC in Patients
with Advanced HIV Infection.” Journal of Acquired Immune De ciency Syndromes and
Human Retrovirology, 11, 161-169.
[13] Hanley, J. A. (1989). “Receiver operating characteristic (ROC) methodology:the state
of the art.” Critical Reviews in Diagnostic Imaging, 29, 307-335.
[14] Heagrty, P. J., Lumley, T. and Pepe, M. S (2000). “Time-dependent ROC curves for
censored survival data and a diagnostic marker.” Biometrics, 56, 337-344.
[15] Henderson, R., Diggle, P. and Dobson, A. (2000). “Joint modeling of longitudinal measurements
and event time data.” Biostatistics, 4, 465-480.
[16] Hosmer, D.W., and Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New
York: Wiley.
[17] knuth84 (Hsieh, F., Tseng, Y. K. and Wang, J. L.). “2006.” Joint Modeling of Survival
and Longitudinal Data: Likelihood Approach Revisited, Biometrics, 62.1037-1043
[18] Jones, M.C. (1990). “The performance of kernel density functions in kernel distribution
function estimation.” Statistics and Probability Letters, 9, 129-132.
[19] Jones, M.C. and Sheather, S.J. (1991). “Using non-stochastic terms to advantage in
kernel-based estimation of integrated squared density derivatives.” Statistics and Prob-
ability Letters, 11, 511-514.
[20] Kaplan, E. L. and Meier, P. (1958). “Nonparametric Estimation from Incomplete Observations.”
Journal of the American Statistical Association, 53, 457-481.
[21] Laird, N. M. andWare, J. H. (1982). “Random-effects models for longitudinal data.” Bio-
metrics, 38, 963-974.
[22] Louis,T. A. (1982). “Finding the observed Fisher information when using the EM algorithm.”
Journal of the Royal Statistical Society, Series B(Methodological), 44, 226-233.
[23] Prentice, R. L. (1982). “Covariate measurement errors and parameter estimation in a
failure time regression model.” Biometrika, 69, 331-342.
[24] Song, X., Davidian, M. and Tsiatis, A. A. (2002). “A Semiparametric Likelihood
Approach to Joint Modeling of Longitudinal and Time-to-Event Data.” Biomet-
rics, 58, 742-753.
[25] Tseng, Y. K., Hsieh F. and Wang, J. L. (2005). “ Joint modeling of accelerated failure
time and longitudinal data.” Biometrika, 92, 587-603.
[26] Tsiatis, A. A. and Davidian, M. (2001). “A semiparametric estimator for the proportional
hazards model with longitudinal covariates measured with error.” Biometrika, 88, 447-
458.
[27] Tsiatis, A. A., Degruttola, V. andWulfsohn, M. S. (1995). “Modeling the Relationship of
Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4
Coutns in Patients with AIDS.” Journal of the American Statistical Association, 90, 27-
37.
[28] Wulfsohn, M. S. and Tsiatis, A. A. (1997). “A Joint Model for Survival and Longitudinal
Data Measured with Error.” Biometrics, 53, 330-339.
[29] Zeng, D. and Cai, J. (2005). “Asymptotic Results for Maximum Likelihood Estimatiors
in Joint Analysis of Repeated Measurements and Survival Time.” The Annals of
Statistics, 33, 2132-2163.
[30] Zeng, D. and Lin, D. Y. (2007a). “Maximum Likelihood Estimation in Semiparametric
Regression Models with Censored Data (with Discussion).” Journal of the Royal
Statistical Society, Series B, 69, 507-564.
[31] Zeng, D. and Lin, D. Y. (2007b). “Efficient Estimation in the Accelerated Failure TimeModel.”
Journal of the American Statistical Association, 102, 1387-1396.
[32] Zweig, M. H. and Campbell, G. (1993). “Receiver-operator characteristic plots: a fundamental
evaluation tool inclinical medicine.” Clinical Chemistry, 39, 561-577.
|
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit