A class of partially linear transformation models for recurrent gap times
From MaRDI portal
Publication:4638739
DOI10.1080/03610926.2017.1313986zbMath1462.62599OpenAlexW2604284561MaRDI QIDQ4638739
Dongxiao Han, Miao Han, Liu-Quan Sun
Publication date: 27 April 2018
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2017.1313986
estimating equationsrecurrent eventsgap timeslocal polynomialspartially linear transformation models
Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Cox's regression model for counting processes: A large sample study
- A flexible semiparametric transformation model for recurrent event data
- Nonparametric modeling of the gap time in recurrent event data
- Hazard models with varying coefficients for multivariate failure time data
- Local likelihood and local partial likelihood in hazard regression
- Marginal regression of gaps between recurrent events
- Efficient estimation of the partly linear additive Cox model
- A class of transformed hazards models for recurrent gap times
- Estimating marginal effects in accelerated failure time models for serial sojourn times among repeated events
- The statistical analysis of recurrent events.
- Marginal regression of multivariate event times based on linear transformation models
- A simple resampling method by perturbing the minimand
- A semiparametric additive rate model for recurrent events with an informative terminal event
- An Estimating Function Approach to the Analysis of Recurrent and Terminal Events
- Quantile Regression for Recurrent Gap Time Data
- Accelerated intensity frailty model for recurrent events data
- A class of mixed models for recurrent event data
- Some Graphical Displays and Marginal Regression Analyses for Recurrent Failure Times and Time Dependent Covariates
- Bivariate Exponential Distributions
- Regression methods for gap time hazard functions of sequentially ordered multivariate failure time data
- Weighted Breslow-type and maximum likelihood estimation in semiparametric transformation models
- Efficient estimation of semiparametric transformation models for counting processes
- The accelerated gap times model
- Accelerated failure time models for counting processes
- Nonparametric estimation of the gap time distribution for serial events with censored data
- Generalized Partially Linear Single-Index Models
- Semiparametric Transformation Models for Point Processes
- Semiparametric analysis of transformation models with censored data
- Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
- Nonparametric Estimation of a Recurrent Survival Function
- Conditional Regression Analysis for Recurrence Time Data
- On Estimation of Partially Linear Transformation Models
- Robust Estimation of Mean Functions and Treatment Effects for Recurrent Events Under Event-Dependent Censoring and Termination: Application to Skeletal Complications in Cancer Metastatic to Bone
- Partially Linear Hazard Regression for Multivariate Survival Data
- Semiparametric Transformation Models With Random Effects for Recurrent Events
- A Joint Frailty Model for Survival and Gap Times Between Recurrent Events
