Marginalized two-part Joint modeling of longitudinal semi-continuous responses and survival data : with application to medical cost

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dc.contributor.author Shahrokhabadi, Mohadeseh Shojaei
dc.contributor.author Chen, Ding-Geng (Din)
dc.contributor.author Mirkamali, Sayed Jamal
dc.contributor.author Kazemnejad, Anoshirvan
dc.contributor.author Zayeri, Farid
dc.date.accessioned 2022-05-24T08:48:38Z
dc.date.available 2022-05-24T08:48:38Z
dc.date.issued 2021-10-15
dc.description.abstract Non-negative continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical costs data. It is thus critical to incorporate the potential dependence of survival status and longitudinal medical costs in joint modeling, where censorship is death-related. Despite the wide use of conventional two-part joint models (CTJMs) to capture zero-inflation, they are limited to conditional interpretations of the regression coefficients in the model’s continuous part. In this paper, we propose a marginalized two-part joint model (MTJM) to jointly analyze semi-continuous longitudinal costs data and survival data. We compare it to the conventional two-part joint model (CTJM) for handling marginal inferences about covariate effects on average costs. We conducted a series of simulation studies to evaluate the superior performance of the proposed MTJM over the CTJM. To illustrate the applicability of the MTJM, we applied the model to a set of real electronic health record (EHR) data recently collected in Iran. We found that the MTJM yielded a smaller standard error, root-mean-square error of estimates, and AIC value, with unbiased parameter estimates. With this MTJM, we identified a significant positive correlation between costs and survival, which was consistent with the simulation results. en_US
dc.description.department Statistics en_US
dc.description.librarian am2022 en_US
dc.description.sponsorship South Africa DST-NRF-SAMRC SARChI Research Chair in Biostatistics en_US
dc.description.uri https://www.mdpi.com/journal/mathematics en_US
dc.identifier.citation Shahrokhabadi, M.S.; Chen, D.-G.; Mirkamali, S.J.; Kazemnejad, A.; Zayeri, F. Marginalized Two-Part Joint Modeling of Longitudinal Semi-Continuous Responses and Survival Data: With Application to Medical Costs. Mathematics 2021, 9, 2603. https://DOI.org/10.3390/math9202603. en_US
dc.identifier.issn 2227-7390
dc.identifier.other 10.3390/math9202603
dc.identifier.uri https://repository.up.ac.za/handle/2263/85642
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.rights © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. en_US
dc.subject Zero-inflated en_US
dc.subject Right-skewed en_US
dc.subject Semi-continuous en_US
dc.subject Proportional hazards model en_US
dc.subject Medical costs data en_US
dc.subject Conventional two-part joint models (CTJMs) en_US
dc.subject Marginalized two-part joint model (MTJM) en_US
dc.subject Electronic health record (EHR) en_US
dc.title Marginalized two-part Joint modeling of longitudinal semi-continuous responses and survival data : with application to medical cost en_US
dc.type Article en_US


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