Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women
Abstract Background Collinearity is a common and problematic phenomenon in studies on public health. It leads to inflation in variance of estimator and reduces test power. This phenomenon can occur in any model. In this study, a new ridge mixed-effects logistic model (RMELM) is proposed to overcome...
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| Format: | Article |
| Language: | English |
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BMC
2021-07-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-021-01325-7 |
| _version_ | 1818359005629644800 |
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| author | Sanaz Khalili Javad Faradmal Hossein Mahjub Babak Moeini Khadijeh Ezzati-Rastegar |
| author_facet | Sanaz Khalili Javad Faradmal Hossein Mahjub Babak Moeini Khadijeh Ezzati-Rastegar |
| author_sort | Sanaz Khalili |
| collection | DOAJ |
| description | Abstract Background Collinearity is a common and problematic phenomenon in studies on public health. It leads to inflation in variance of estimator and reduces test power. This phenomenon can occur in any model. In this study, a new ridge mixed-effects logistic model (RMELM) is proposed to overcome consequences of collinearity in correlated binary responses. Methods Parameters were estimated through penalized log-likelihood with combining expectation maximization (EM) algorithm, gradient ascent, and Fisher-scoring methods. A simulation study was performed to compare new model with mixed-effects logistic model(MELM). Mean square error, relative bias, empirical power, and variance of random effects were used to evaluate RMELM. Also, contribution of various types of violence, and intervention on depression among pregnant women experiencing intimate partner violence(IPV) were analyzed by new and previous models. Results Simulation study showed that mean square errors of fixed effects were decreased for RMELM than MELM and empirical power were increased. Inflation in variance of estimators due to collinearity was clearly shown in the MELM in data on IPV and RMELM adjusted the variances. Conclusions According to simulation results and analyzing IPV data, this new estimator is appropriate to deal with collinearity problems in the modelling of correlated binary responses. |
| first_indexed | 2024-12-13T20:38:01Z |
| format | Article |
| id | doaj.art-4d9a76c54650411ca29dfef1b5361ce8 |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-13T20:38:01Z |
| publishDate | 2021-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-4d9a76c54650411ca29dfef1b5361ce82022-12-21T23:32:14ZengBMCBMC Medical Research Methodology1471-22882021-07-012111810.1186/s12874-021-01325-7Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant womenSanaz Khalili0Javad Faradmal1Hossein Mahjub2Babak Moeini3Khadijeh Ezzati-Rastegar4Department of Biostatistics School of Public Health, Hamadan University of Medical SciencesDepartment of Biostatistics School of Public Health, Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical SciencesDepartment of Biostatistics School of Public Health, Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical SciencesSocial Determinants of Health Research Center, Hamadan University of Medical SciencesHealth Education and Promotion, Department of Public Health, Hamadan University of Medical SciencesAbstract Background Collinearity is a common and problematic phenomenon in studies on public health. It leads to inflation in variance of estimator and reduces test power. This phenomenon can occur in any model. In this study, a new ridge mixed-effects logistic model (RMELM) is proposed to overcome consequences of collinearity in correlated binary responses. Methods Parameters were estimated through penalized log-likelihood with combining expectation maximization (EM) algorithm, gradient ascent, and Fisher-scoring methods. A simulation study was performed to compare new model with mixed-effects logistic model(MELM). Mean square error, relative bias, empirical power, and variance of random effects were used to evaluate RMELM. Also, contribution of various types of violence, and intervention on depression among pregnant women experiencing intimate partner violence(IPV) were analyzed by new and previous models. Results Simulation study showed that mean square errors of fixed effects were decreased for RMELM than MELM and empirical power were increased. Inflation in variance of estimators due to collinearity was clearly shown in the MELM in data on IPV and RMELM adjusted the variances. Conclusions According to simulation results and analyzing IPV data, this new estimator is appropriate to deal with collinearity problems in the modelling of correlated binary responses.https://doi.org/10.1186/s12874-021-01325-7CollinearityMixed-effects logistic modelRidge estimatorViolence |
| spellingShingle | Sanaz Khalili Javad Faradmal Hossein Mahjub Babak Moeini Khadijeh Ezzati-Rastegar Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women BMC Medical Research Methodology Collinearity Mixed-effects logistic model Ridge estimator Violence |
| title | Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women |
| title_full | Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women |
| title_fullStr | Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women |
| title_full_unstemmed | Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women |
| title_short | Overcoming the problems caused by collinearity in mixed-effects logistic model: determining the contribution of various types of violence on depression in pregnant women |
| title_sort | overcoming the problems caused by collinearity in mixed effects logistic model determining the contribution of various types of violence on depression in pregnant women |
| topic | Collinearity Mixed-effects logistic model Ridge estimator Violence |
| url | https://doi.org/10.1186/s12874-021-01325-7 |
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