1 |
Andersen, P. K., Geskus, R. B., de Witte, T., and Putter, H. (2012). Competing risks in epidemiology:possibilities and pitfalls, International Journal of Epidemiology, 41, 861-870.
DOI
|
2 |
Barrett, J. K., Siannis, F., and Farewell, V. T. (2011). A semi-competing risks model for data with intervalcensoring and informative observation: An application to the MRC cognitive function and aging study, Statistics in Medicine, 30, 1-10.
DOI
|
3 |
Cox, D. R. (1972). Models and life-tables regression, Journal of the Royal Statistical Society, Series B, 34, 187-220.
|
4 |
Cox, D. R. (1975). Partial likelihood, Biometrika, 62, 269-276.
DOI
|
5 |
Fine, J. P., Jiang, H., and Chappell, R. (2001). On semi-competing risks data, Biometrika, 88, 907-919.
DOI
|
6 |
Frydman, H., Gerds, T., Gron, R., and Keiding, N. (2013). Nonparametric estimation in an "illness-death" model when all transition times are interval censored, Biomedical Journal, 55, 823-843.
|
7 |
Helmer, C., Joly, P., Letenneur, L., Commenges, D., and Dartigues, J. F. (2001). Mortality with dementia:results from a French prospective community-based cohort, American Journal of Epidemiology, 154, 642-648.
DOI
|
8 |
Joly, P., Commenges, D., Helmer, C., and Letenneur, L. (2002). A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia, Biostatistics, 3, 433-443.
DOI
|
9 |
Kim, J. and Kim, J. (2016). Regression models for interval-censored semi-competing risks data with missing intermediate transition status, The Korean Journal of Applied Statistics, 29, 1311-1327.
DOI
|
10 |
Kim, J., Kim, J., and Kim, S. W. (2019). Additive-multiplicative hazards regression models for intervalcensored semi-competing risks data with missing intermediate events, BMC Medical Research Methodology, 19, 1-14.
DOI
|
11 |
Lee, K. H., Lee, C., Alvares, D., and Haneuse, S. (2019). Hierarchical models for parametric and semiparametric analyses of semi-competing risks data. Available from: https://CRAN.R-project.org/package=SemiCompRisks
|
12 |
Leffondre, K., Touraine, C., Helmer, C., and Joly, P. (2013). Interval-censored time-to-event and competing risk with death: is the illness-death model more accurate than the Cox model?, International Journal of Epidemiology, 42, 1177-1186.
DOI
|
13 |
Pinheiro, J. C. and Bates, D. M. (1995). Approximations to the log-likelihood function in the nonlinear mixed-effects model, Journal of Computational and Graphical Statistics, 4, 12-35.
DOI
|
14 |
Tsiatis, A. A. (2005). Competing risks, Encyclopedia of Biostatistics, 2, 1025-1035.
|
15 |
Putter, H., Fiocco, M., and Geskus, R. B. (2007). Tutorial in biostatistics: competing risks and multi-state models, Statistics in Medicine, 26, 2389-2430.
DOI
|
16 |
Siannis, F., Farewell, V. T., and Head, J. (2007). A multi-state model for joint modelling of terminal and non-terminal events with application to Whitehall II, Statistics in Medicine, 26, 426-442.
DOI
|
17 |
Touraine, C., Gerds, T. A., and Joly, P. (2014). SmoothHazard: An R package for fitting regression models to interval-censored observations of illness-death models, Journal of Statistical Software, 79, 1-22.
|
18 |
Wellner, J. A. and Zhan, Y. (1997). A hybrid algorithm for computation of the nonparametric maximum likelihood estimator from censored data, Journal of the American Statistical Association, 92, 945-959.
DOI
|
19 |
Xu, J., Kalbfleisch, J. D., and Tai, B. (2010). Statistical analysis of illness-death processes and semicompeting risks data, Biometrics, 66, 716-725.
DOI
|