The package offers a comprehensive collection ofpractical and easy-to-use tools for analyzing recurrent event data, with or withoutthe presence of a (possibly) correlated terminal event. The modeling framework is basedon a joint frailty scale-change model, that encompasses many existing models, including the popular Cox-type models, as special cases and accommodates informative censoring through a subject-specific frailty. The implemented estimating procedure does not require any parametric assumption on the frailty distribution. The package allows the users to specify different model forms for both the recurrent event process and the terminal event. The package also included are visualization of recurrent events and simulation from the regression models.
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Ghosh, D. and Lin, D.Y. (2002). Marginal Regression Models for Recurrent and Terminal Events. Statistica Sinica: 663--688.
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Xu, G., Chiou, S.H., Huang, C.-Y., Wang, M.-C. and Yan, J. (2017). Joint Scale-change Models for Recurrent Events and Failure Time. Journal of the American Statistical Association, 112(518): 796--805.
Xu, G., Chiou, S.H.,Yan, J., Marr, K., and Huang, C.-Y. (2019). Generalized Scale-Change Models for Recurrent Event Processes under Informative Censoring. Statistica Sinica: pre-print.
Maintainer: Sy Han (Steven) Chiou email@example.com
Chiung-Yu Huang ChiungYu.Huang@ucsf.edu