Robust Regression Analysis for Clustered Interval-Censored Failure Time Data

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 ro...

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Bibliographic Details
Published inJournal of systems science and complexity Vol. 34; no. 3; pp. 1156 - 1174
Main Authors Luo, Lin, Zhao, Hui
Format Journal Article
LanguageEnglish
Published Beijing Academy of Mathematics and Systems Science, Chinese Academy of Sciences 01.06.2021
Springer Nature B.V
Subjects
Complex Systems
Control
Failure analysis
Failure times
Mathematics
Mathematics and Statistics
Mathematics of Computing
Operations Research/Decision Theory
Parameter estimation
Regression analysis
Robustness (mathematics)
Statistical analysis
Statistics
Systems Theory
random effects
Clustered data
rank estimation
interval-censoring
semiparametric transformation models
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Summary: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.
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ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-020-9350-2