A semi-parametric approach to analysis of event duration and prevalence

DOI10.1016/J.CSDA.2013.05.023zbMath1471.62208OpenAlexW1976396117MaRDI QIDQ1615116

George Quartey, Jixian Wang

Publication date: 2 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2013.05.023

zbMATH Keywords

prevalencerecurrent eventstime-varying coefficientsemi-parametric model

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• SAS
• SAS/STAT

Cites Work

• Modeling gap times between recurrent events by marginal rate function
• Cox's regression model for counting processes: A large sample study
• The statistical analysis of recurrent events.
• Nonparametric estimation for cumulative duration of adverse events
• Temporal process regression
• The Robust Inference for the Cox Proportional Hazards Model
• Analysis of Episodic Data With Application to Recurrent Pulmonary Exacerbations in Cystic Fibrosis Patients
• Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
• Marginal Regression Models for Multivariate Failure Time Data
• Some Simple Robust Methods for the Analysis of Recurrent Events
• Multi-state models for event history analysis
• Multi-state models for bone marrow transplantation studies
• Analysis of repeated events
• Dose-Finding Based on Multiple Toxicities in a Soft Tissue Sarcoma Trial

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