Bayesian inference for nonlinear mixed-effects location scale and interval-censoring cure-survival models: An application to pregnancy miscarriage
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| Názov: | Bayesian inference for nonlinear mixed-effects location scale and interval-censoring cure-survival models: An application to pregnancy miscarriage |
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| Autori: | Danilo Alvares, Cristian Meza, Rolando De la Cruz |
| Prispievatelia: | Apollo - University of Cambridge Repository |
| Zdroj: | Statistical Methods in Medical Research. 34:1525-1533 |
| Informácie o vydavateľovi: | SAGE Publications, 2025. |
| Rok vydania: | 2025 |
| Predmety: | longitudinal data, three-parameter logistic model, Models, Statistical, mixed-effects location scale, Bayes Theorem, Survival Analysis, Abortion, Spontaneous, Joint models, Nonlinear Dynamics, Pregnancy, time-to-event, Humans, Female, Computer Simulation, Longitudinal Studies |
| Popis: | Motivated by a pregnancy miscarriage study, we propose a Bayesian joint model for longitudinal and time-to-event outcomes that takes into account different complexities of the problem. In particular, the longitudinal process is modeled by means of a nonlinear specification with subject-specific error variance. In addition, the exact time of fetal death is unknown, and a subgroup of women is not susceptible to miscarriage. Hence, we model the survival process via a mixture cure model for interval-censored data. Finally, both processes are linked through the subject-specific longitudinal mean and variance. A simulation study is conducted in order to validate our joint model. In the real application, we use individual weighted and Cox-Snell residuals to assess the goodness-of-fit of our proposal versus a joint model that shares only the subject-specific longitudinal mean (standard approach). In addition, the leave-one-out cross-validation criterion is applied to compare the predictive ability of both models. |
| Druh dokumentu: | Article |
| Popis súboru: | application/pdf; text/xml |
| Jazyk: | English |
| ISSN: | 1477-0334 0962-2802 |
| DOI: | 10.1177/09622802251345485 |
| Rights: | CC BY |
| Prístupové číslo: | edsair.doi.dedup.....b9898e17d97c94cd1ee8e78817fa012b |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | Motivated by a pregnancy miscarriage study, we propose a Bayesian joint model for longitudinal and time-to-event outcomes that takes into account different complexities of the problem. In particular, the longitudinal process is modeled by means of a nonlinear specification with subject-specific error variance. In addition, the exact time of fetal death is unknown, and a subgroup of women is not susceptible to miscarriage. Hence, we model the survival process via a mixture cure model for interval-censored data. Finally, both processes are linked through the subject-specific longitudinal mean and variance. A simulation study is conducted in order to validate our joint model. In the real application, we use individual weighted and Cox-Snell residuals to assess the goodness-of-fit of our proposal versus a joint model that shares only the subject-specific longitudinal mean (standard approach). In addition, the leave-one-out cross-validation criterion is applied to compare the predictive ability of both models. |
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| ISSN: | 14770334 09622802 |
| DOI: | 10.1177/09622802251345485 |