Panel count data are frequently encountered when study subjects are under discrete observations.However,limited literature has been found on variable selection for panel count data.In this paper,without considering th...Panel count data are frequently encountered when study subjects are under discrete observations.However,limited literature has been found on variable selection for panel count data.In this paper,without considering the model assumption of observation process,a more general semiparametric transformation model for panel count data with informative observation process is developed.A penalized estimation procedure based on the quantile regression function is proposed for variable selection and parameter estimation simultaneously.The consistency and oracle properties of the estimators are established under some mild conditions.Some simulations and an application are reported to evaluate the proposed approach.展开更多
Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and ma...Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based on rank correlation to estimate the unknown parameters. The large sample properties of the estimator are also established. In addition, the authors illustrate the performance of the proposed estimate with extensive simulations and two real data examples.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant No.12001485the National Bureau of Statistics of China under Grant No.2020LY073the First Class Discipline of Zhejiang-A(Zhejiang University of Finance and Economics-Statistics)under Grant No.Z0111119010/024。
文摘Panel count data are frequently encountered when study subjects are under discrete observations.However,limited literature has been found on variable selection for panel count data.In this paper,without considering the model assumption of observation process,a more general semiparametric transformation model for panel count data with informative observation process is developed.A penalized estimation procedure based on the quantile regression function is proposed for variable selection and parameter estimation simultaneously.The consistency and oracle properties of the estimators are established under some mild conditions.Some simulations and an application are reported to evaluate the proposed approach.
基金supported by the National Natural Science Foundation of China under Grant Nos. 11471135and 11861030。
文摘Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based on rank correlation to estimate the unknown parameters. The large sample properties of the estimator are also established. In addition, the authors illustrate the performance of the proposed estimate with extensive simulations and two real data examples.
