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Full Description
This book primarily aims to discuss emerging topics in statistical methods and to booster research, education, and training to advance statistical modeling on interval-censored survival data. Commonly collected from public health and biomedical research, among other sources, interval-censored survival data can easily be mistaken for typical right-censored survival data, which can result in erroneous statistical inference due to the complexity of this type of data. The book invites a group of internationally leading researchers to systematically discuss and explore the historical development of the associated methods and their computational implementations, as well as emerging topics related to interval-censored data. It covers a variety of topics, including univariate interval-censored data, multivariate interval-censored data, clustered interval-censored data, competing risk interval-censored data, data with interval-censored covariates, interval-censored data from electric medical records, and misclassified interval-censored data. Researchers, students, and practitioners can directly make use of the state-of-the-art methods covered in the book to tackle their problems in research, education, training and consultation.
Contents
- Part I Introduction and Review. - Overview of Historical Developments in Modeling Interval-Censored Survival Data. - Overview of Recent Advances on the Analysis of Interval-Censored Failure Time Data. - Predictive Accuracy of Prediction Model for Interval-Censored Data. - Part II Emerging Topics in Methodology. - A Practical Guide to Exact Confidence Intervals for a Distribution of Current Status Data Using the Binomial Approach. - Accelerated Hazards Model and Its Extensions for Interval-Censored Data. - Maximum Likelihood Estimation of Semiparametric Regression Models with Interval-Censored Data. - Use of the INLA Approach for the Analysis of Interval-Censored Data. - Copula Models and Diagnostics for Multivariate Interval-Censored Data. - Efficient Estimation of the Additive Risks Model for Interval-Censored Data. - Part III Emerging Topics in Applications. - Modeling and Analysis of Chronic Disease Processes Under Intermittent Observation. - Case-Cohort Studies with Time-Dependent Covariates and Interval-Censored Outcome. - The BivarIntCensored: An R Package for Nonparametric Inference of Bivariate Interval-Censored Data. - Joint Modeling for Longitudinal and Interval-Censored Survival Data: Application to IMPI Multi-Center HIV/AIDS Clinical Trial. - Regression Analysis with Interval-Censored Covariates. Application to Liquid Chromatography. - Misclassification Simulation Extrapolation Procedure for Interval-Censored Log-Logistic Accelerated Failure Time Model.
