Copula-frailty models for recurrent event data based on Monte Carlo EM algorithm

Multi-type recurrent events are often encountered in medical applications when two or more different event types could repeatedly occur over an observation period. For example, patients may experience recurrences of multi-type nonmelanoma skin cancers in a clinical trial for skin cancer prevention....

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Bibliographic Details
Published inJournal of statistical computation and simulation Vol. 91; no. 17; pp. 3530 - 3548
Main Authors Bedair, Khaled F., Hong, Yili, Al-Khalidi, Hussein R.
Format Journal Article
LanguageEnglish
Published Taylor & Francis 22.11.2021
Subjects
Clinical trial
MCEM algorithm
multi-type recurrences
multivariate frailty
skin cancers
survival models
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Summary:Multi-type recurrent events are often encountered in medical applications when two or more different event types could repeatedly occur over an observation period. For example, patients may experience recurrences of multi-type nonmelanoma skin cancers in a clinical trial for skin cancer prevention. The aims in those applications are to characterize features of the marginal processes, evaluate covariate effects, and quantify both the within-subject recurrence dependence and the dependence among different event types. We use copula-frailty models to analyze correlated recurrent events of different types. Parameter estimation and inference are carried out by using a Monte Carlo expectation-maximization (MCEM) algorithm, which can handle a relatively large (i.e. three or more) number of event types. Performances of the proposed methods are evaluated via extensive simulation studies. The developed methods are used to model the recurrences of skin cancer with different types.
ISSN:0094-9655
1563-5163
DOI:10.1080/00949655.2021.1942471