1 |
Andersen, P. K., Borgan, O., Gill, R. D., and Keiding, N. (1993). Statistical Models Based on Counting Processes, Springer, New York.
|
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 |
Collett, D. (2015). Modeling Survival Data in Medical Research (3rd ed), CRC Press, London.
|
4 |
Cox, D. R. (1972). Regression models and life-tables, Journal of the Royal Statistical Society, Series B (Methodological), 34, 187-220.
|
5 |
Frydman, H. and Szarek, M. (2009). Nonparametric estimation in a Markov "illness-death" process from interval censored observations with missing intermediate transition status, Biometrics, 65, 143-151.
DOI
|
6 |
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
|
7 |
Joly, P., Commenges, D., and Letenneur, L. (1998). A penalized likelihood approach for arbitrarily censored and truncated data: application to age-specific incidence of dementia, Biometrics, 54, 185-194.
DOI
|
8 |
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
|
9 |
Lin, D. Y. and Ying, Z. (1994). Semiparametric analysis of the additive risk model, Biometrika, 81, 61-71.
DOI
|
10 |
Lin, D. Y. and Ying, Z. (1995). Semiparametric analysis of general additive-multiplicative hazard models for counting processes, The Annals of Statistics, 23, 1712-1734.
DOI
|
11 |
Lindsey, J. C. and Ryan, L. M. (1998). Tutorial in biostatistics: Methods for interval-censored data, Statistics in Medicine, 17, 219-238.
DOI
|
12 |
MRC CFAS (1998). Cognitive function and dementia in six areas of England and Wales: the distribution of MMSE and prevalence of GMS organicity level in the MRC CFA Study. The Medical Research Council Cognitive Function and Ageing Study (MRC CFAS), Psychological Medicine, 28, 319-335.
DOI
|
13 |
Touraine, C., Joly, P., and Gerds, T. A. (2014). SmoothHazards: Fitting illness-death model for interval-censored data, R package version 1.2.3, from: https://www.R-project.org/package=SmoothHazard
|
14 |
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.
|
15 |
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
|