Modified generalized method of moments for a robust estimation of polytomous logistic model
The maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2014-07-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/467.pdf |
| _version_ | 1797418804214497280 |
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| author | Xiaoshan Wang |
| author_facet | Xiaoshan Wang |
| author_sort | Xiaoshan Wang |
| collection | DOAJ |
| description | The maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM) approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness. |
| first_indexed | 2024-03-09T06:39:17Z |
| format | Article |
| id | doaj.art-6b57f909557a4d4ba5320351a1b892ac |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:39:17Z |
| publishDate | 2014-07-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-6b57f909557a4d4ba5320351a1b892ac2023-12-03T10:54:15ZengPeerJ Inc.PeerJ2167-83592014-07-012e46710.7717/peerj.467467Modified generalized method of moments for a robust estimation of polytomous logistic modelXiaoshan Wang0Department of Clinical and Translational Research/Forsyth Institute, Cambridge, MA, USAThe maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM) approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.https://peerj.com/articles/467.pdfRobust statisticsGeneralized method of weighted momentsPolytomous logistic model |
| spellingShingle | Xiaoshan Wang Modified generalized method of moments for a robust estimation of polytomous logistic model PeerJ Robust statistics Generalized method of weighted moments Polytomous logistic model |
| title | Modified generalized method of moments for a robust estimation of polytomous logistic model |
| title_full | Modified generalized method of moments for a robust estimation of polytomous logistic model |
| title_fullStr | Modified generalized method of moments for a robust estimation of polytomous logistic model |
| title_full_unstemmed | Modified generalized method of moments for a robust estimation of polytomous logistic model |
| title_short | Modified generalized method of moments for a robust estimation of polytomous logistic model |
| title_sort | modified generalized method of moments for a robust estimation of polytomous logistic model |
| topic | Robust statistics Generalized method of weighted moments Polytomous logistic model |
| url | https://peerj.com/articles/467.pdf |
| work_keys_str_mv | AT xiaoshanwang modifiedgeneralizedmethodofmomentsforarobustestimationofpolytomouslogisticmodel |