Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference
Abstract Semi-continuous data characterized by an excessive proportion of zeros and right-skewed continuous positive values appear frequently in medical research. One example would be the pharmaceutical expenditure (PE) data for which a substantial proportion of subjects investigated may report zero...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-11-01
|
| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12874-022-01736-0 |
| _version_ | 1811233759006031872 |
|---|---|
| author | Naser Kamyari Ali Reza Soltanian Hossein Mahjub Abbas Moghimbeigi Maryam Seyedtabib |
| author_facet | Naser Kamyari Ali Reza Soltanian Hossein Mahjub Abbas Moghimbeigi Maryam Seyedtabib |
| author_sort | Naser Kamyari |
| collection | DOAJ |
| description | Abstract Semi-continuous data characterized by an excessive proportion of zeros and right-skewed continuous positive values appear frequently in medical research. One example would be the pharmaceutical expenditure (PE) data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyse clustered measures of semi-continuous data from multilevel studies. In this study, we propose a new flexible two-part mixed-effects model with skew distributions for nested semi-continuous cost data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: Part I) a model on the occurrence of positive values using a generalized logistic mixed model; and Part II) a model on the magnitude of positive values using a linear mixed model where the model errors follow skew distributions including beta-prime (BP). The proposed method is illustrated with pharmaceutical expenditure data from a multilevel observational study and the analytic results are reported by comparing potential models under different skew distributions. Simulation studies are conducted to assess the performance of the proposed model. The DIC3, LPML, WAIC, and LOO as the Bayesian model selection criteria and measures of divergence used to compare the models. |
| first_indexed | 2024-04-12T11:24:37Z |
| format | Article |
| id | doaj.art-bc23ce29d2d3420faf4bba8f208647b9 |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-04-12T11:24:37Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-bc23ce29d2d3420faf4bba8f208647b92022-12-22T03:35:15ZengBMCBMC Medical Research Methodology1471-22882022-11-0122111510.1186/s12874-022-01736-0Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inferenceNaser Kamyari0Ali Reza Soltanian1Hossein Mahjub2Abbas Moghimbeigi3Maryam Seyedtabib4Department of Biostatistics and Epidemiology, School of Health, Abadan University of Medical SciencesModeling of Noncommunicable Diseases Research Center, Hamadan University of Medical SciencesResearch Center for Health Sciences, School of Public Health, Hamadan University of Medical SciencesDepartment of Biostatistics and Epidemiology, School of Health, Research Center for Health, Safety and Environment, Alborz University of Medical SciencesDepartment of Biostatistics and Epidemiology, School of Health, Ahvaz Jundishapur University of Medical SciencesAbstract Semi-continuous data characterized by an excessive proportion of zeros and right-skewed continuous positive values appear frequently in medical research. One example would be the pharmaceutical expenditure (PE) data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyse clustered measures of semi-continuous data from multilevel studies. In this study, we propose a new flexible two-part mixed-effects model with skew distributions for nested semi-continuous cost data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: Part I) a model on the occurrence of positive values using a generalized logistic mixed model; and Part II) a model on the magnitude of positive values using a linear mixed model where the model errors follow skew distributions including beta-prime (BP). The proposed method is illustrated with pharmaceutical expenditure data from a multilevel observational study and the analytic results are reported by comparing potential models under different skew distributions. Simulation studies are conducted to assess the performance of the proposed model. The DIC3, LPML, WAIC, and LOO as the Bayesian model selection criteria and measures of divergence used to compare the models.https://doi.org/10.1186/s12874-022-01736-0Bayesian frameworkNon-negative dataTwo-part mixed-effects modelSkew distributionsPharmaceutical expenditure |
| spellingShingle | Naser Kamyari Ali Reza Soltanian Hossein Mahjub Abbas Moghimbeigi Maryam Seyedtabib Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference BMC Medical Research Methodology Bayesian framework Non-negative data Two-part mixed-effects model Skew distributions Pharmaceutical expenditure |
| title | Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference |
| title_full | Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference |
| title_fullStr | Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference |
| title_full_unstemmed | Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference |
| title_short | Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference |
| title_sort | zero augmented beta prime model for multilevel semi continuous data a bayesian inference |
| topic | Bayesian framework Non-negative data Two-part mixed-effects model Skew distributions Pharmaceutical expenditure |
| url | https://doi.org/10.1186/s12874-022-01736-0 |
| work_keys_str_mv | AT naserkamyari zeroaugmentedbetaprimemodelformultilevelsemicontinuousdataabayesianinference AT alirezasoltanian zeroaugmentedbetaprimemodelformultilevelsemicontinuousdataabayesianinference AT hosseinmahjub zeroaugmentedbetaprimemodelformultilevelsemicontinuousdataabayesianinference AT abbasmoghimbeigi zeroaugmentedbetaprimemodelformultilevelsemicontinuousdataabayesianinference AT maryamseyedtabib zeroaugmentedbetaprimemodelformultilevelsemicontinuousdataabayesianinference |