The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.]
Multicollinearity is a case of multiple regression in which the predictor variables are highly correlated among themselves. The problem will get more complicated when multicollinearity exists together with high leverage points. The usage of classical VIF for multicollinearity diagnostics is not reli...
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| Format: | Article |
| Language: | English |
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Unit Penerbitan UiTM Kelantan
2016
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| Online Access: | https://ir.uitm.edu.my/id/eprint/24199/1/9-Article%20Text-34-1-10-20181104%20-%20Combine%20Cover.pdf |
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| author | Ibrahim, Nurul Bariyah Midi, Habshah (Prof Dr.) Noor Ilanie Nordin, Noor Ilanie Ismail, Nor Azima Jauhari, Nur Elini Mohamad Sobri, Norafefah |
| author_facet | Ibrahim, Nurul Bariyah Midi, Habshah (Prof Dr.) Noor Ilanie Nordin, Noor Ilanie Ismail, Nor Azima Jauhari, Nur Elini Mohamad Sobri, Norafefah |
| author_sort | Ibrahim, Nurul Bariyah |
| collection | UITM |
| description | Multicollinearity is a case of multiple regression in which the predictor variables are highly correlated among themselves. The problem will get more complicated when multicollinearity exists together with high leverage points. The usage of classical VIF for multicollinearity diagnostics is not reliable as it is not resistant to the presence of high leverage points. In this study, we proposed RVIF which is based on the MM estimator in the detection of multicollinearity due to the high leverage point. The computation of RVIF is based on robust coefficient determination which is called RR2 (MM). We denote this estimator as RVIF (MM). The numerical results and Monte Carlo simulation study indicate that the CVIF performs poorly in the presence of high leverage point and the proposed RVIF is very resistant to the high leverage point and unable to detect the multicollinearity in the data. |
| first_indexed | 2024-03-06T01:56:31Z |
| format | Article |
| id | uitm.eprints-4199 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T01:56:31Z |
| publishDate | 2016 |
| publisher | Unit Penerbitan UiTM Kelantan |
| record_format | dspace |
| spelling | uitm.eprints-41992020-03-30T16:51:43Z https://ir.uitm.edu.my/id/eprint/24199/ The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] jmcs Ibrahim, Nurul Bariyah Midi, Habshah (Prof Dr.) Noor Ilanie Nordin, Noor Ilanie Ismail, Nor Azima Jauhari, Nur Elini Mohamad Sobri, Norafefah Factor analysis. Principal components analysis. Correspondence analysis Analysis Multicollinearity is a case of multiple regression in which the predictor variables are highly correlated among themselves. The problem will get more complicated when multicollinearity exists together with high leverage points. The usage of classical VIF for multicollinearity diagnostics is not reliable as it is not resistant to the presence of high leverage points. In this study, we proposed RVIF which is based on the MM estimator in the detection of multicollinearity due to the high leverage point. The computation of RVIF is based on robust coefficient determination which is called RR2 (MM). We denote this estimator as RVIF (MM). The numerical results and Monte Carlo simulation study indicate that the CVIF performs poorly in the presence of high leverage point and the proposed RVIF is very resistant to the high leverage point and unable to detect the multicollinearity in the data. Unit Penerbitan UiTM Kelantan 2016-06 Article NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/24199/1/9-Article%20Text-34-1-10-20181104%20-%20Combine%20Cover.pdf The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.]. (2016) Journal of Mathematics and Computing Science (JMCS) <https://ir.uitm.edu.my/view/publication/Journal_of_Mathematics_and_Computing_Science_=28JMCS=29/>, 1 (1). pp. 30-37. ISSN 0128-0767 https://jmcs.com.my/ |
| spellingShingle | Factor analysis. Principal components analysis. Correspondence analysis Analysis Ibrahim, Nurul Bariyah Midi, Habshah (Prof Dr.) Noor Ilanie Nordin, Noor Ilanie Ismail, Nor Azima Jauhari, Nur Elini Mohamad Sobri, Norafefah The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title | The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title_full | The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title_fullStr | The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title_full_unstemmed | The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title_short | The effect of high leverage points on VIF measures on noncollinear data / Nurul Bariyah Ibrahim... [et al.] |
| title_sort | effect of high leverage points on vif measures on noncollinear data nurul bariyah ibrahim et al |
| topic | Factor analysis. Principal components analysis. Correspondence analysis Analysis |
| url | https://ir.uitm.edu.my/id/eprint/24199/1/9-Article%20Text-34-1-10-20181104%20-%20Combine%20Cover.pdf |
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