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dc.contributor.author | Shahrokhabadi, Mohadeseh Shojaei![]() |
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dc.contributor.author | Chen, Ding-Geng (Din)![]() |
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dc.contributor.author | Mirkamali, Sayed Jamal![]() |
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dc.contributor.author | Kazemnejad, Anoshirvan![]() |
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dc.contributor.author | Zayeri, Farid![]() |
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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 |