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>Monotone spline-based least squares estimation for panel count data with informative observation times
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Monotone spline-based least squares estimation for panel count data with informative observation times
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机译:基于单调样条的最小二乘估计,用于面板计数数据,提供有益的观察时间
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摘要
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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