Monotone spline‐based least squares estimation for panel count data with informative observation times |
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Authors: | Shirong Deng Li Liu Xingqiu Zhao |
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Institution: | 1. School of Mathematics and Statistics, Wuhan University, Wuhan, China;2. Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China |
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Abstract: | This article discusses the statistical analysis of panel count data when the underlying recurrent event process and observation process may be correlated. For the recurrent event process, we propose a new class of semiparametric mean models that allows for the interaction between the observation history and covariates. For inference on the model parameters, a monotone spline‐based least squares estimation approach is developed, and the resulting estimators are consistent and asymptotically normal. In particular, our new approach does not rely on the model specification of the observation process. The proposed inference procedure performs well through simulation studies, and it is illustrated by the analysis of bladder tumor data. |
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Keywords: | Informative observation process Least squares estimation Monotone B‐splines Panel count data Semiparametric mean models |
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