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

TY - JOUR

T1 - Copula-frailty models for recurrent event data based on Monte Carlo EM algorithm

AU - Bedair, Khaled F.

AU - Hong, Yili

AU - Al-Khalidi, Hussein R.

N1 - Funding Information: The authors thank the editor, associate editor, and referee, for their valuable comments that helped in improving the paper significantly. The authors acknowledge Advanced Research Computing at Virginia Tech for providing computational resources. The work by Hong was partially supported by National Science Foundation Grant CMMI-1904165 to Virginia Tech. Publisher Copyright: © 2021 Informa UK Limited, trading as Taylor & Francis Group.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Clinical trial

KW - MCEM algorithm

KW - multi-type recurrences

KW - multivariate frailty

KW - skin cancers

KW - survival models

UR - https://www.scopus.com/pages/publications/85108626334

U2 - 10.1080/00949655.2021.1942471

DO - 10.1080/00949655.2021.1942471

M3 - Article

AN - SCOPUS:85108626334

SN - 0094-9655

VL - 91

SP - 3530

EP - 3548

JO - Journal of Statistical Computation and Simulation

JF - Journal of Statistical Computation and Simulation

IS - 17

ER -