A class of Box-Cox transformation models for recurrent event data |
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Authors: | Liuquan Sun Xingwei Tong Xian Zhou |
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Institution: | 1.Institute of Applied Mathematics, Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,People’s Republic of China;2.School of Mathematical Sciences,Beijing Normal University,Beijing,People’s Republic of China;3.Department of Actuarial Studies,Macquarie University,Sydney,Australia |
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Abstract: | In this article, we propose a class of Box-Cox transformation models for recurrent event data, which includes the proportional
means models as special cases. The new model offers great flexibility in formulating the effects of covariates on the mean
functions of counting processes while leaving the stochastic structure completely unspecified. For the inference on the proposed
models, we apply a profile pseudo-partial likelihood method to estimate the model parameters via estimating equation approaches
and establish large sample properties of the estimators and examine its performance in moderate-sized samples through simulation
studies. In addition, some graphical and numerical procedures are presented for model checking. An example of application
on a set of multiple-infection data taken from a clinic study on chronic granulomatous disease (CGD) is also illustrated. |
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