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• W2890588401 abstract "We propose a joint modeling likelihood-based approach for studies with repeated measures and informative right censoring. Joint modeling of longitudinal and survival data are common approaches but could result in biased estimates if proportionality of hazards is violated. To overcome this issue, and given that the exact time of dropout is typically unknown, we modeled the censoring time as the number of follow-up visits and extended it to be dependent on selected covariates. Longitudinal trajectories for each subject were modeled to provide insight into disease progression and incorporated with the number follow-up visits in one likelihood function." @default.
• W2890588401 created "2018-09-27" @default.
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• W2890588401 date "2018-09-19" @default.
• W2890588401 modified "2023-10-15" @default.
• W2890588401 title "A likelihood based approach for joint modeling of longitudinal trajectories and informative censoring process" @default.
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• W2890588401 doi "https://doi.org/10.1080/03610926.2018.1473599" @default.
• W2890588401 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6768558" @default.
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