Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.]
Inaccurate and invalid statistical inferences in regression analysis may be caused by multicollinearity due to the presence of high leverage points (HLP) in a data set. Therefore, it is important that high leverage point which is a form ofoutlier be detected because its existence can lead to misfitt...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Research Management Institute (RMI)
2010
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| Online Access: | https://ir.uitm.edu.my/id/eprint/13085/ |
| _version_ | 1848803235828072448 |
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| author | Mohamed Ramli, Norazan Mahmud, Zamalia Zakaria, Husein Idris, Mohammad Radzi Abdul Aziz, Alizan |
| author_facet | Mohamed Ramli, Norazan Mahmud, Zamalia Zakaria, Husein Idris, Mohammad Radzi Abdul Aziz, Alizan |
| author_sort | Mohamed Ramli, Norazan |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Inaccurate and invalid statistical inferences in regression analysis may be caused by multicollinearity due to the presence of high leverage points (HLP) in a data set. Therefore, it is important that high leverage point which is a form ofoutlier be detected because its existence can lead to misfitting of a regression model, thus resulting in inaccuracy of regression results. In this paper, several methods have been proposed to identify HLP in a financial
accounting data set prior to conducting further analysis of regression and other multivariate analysis. The Pearson scorrelation coefficient and variance inflation factors (VIF) were used to measure the success of a detection method. Numerical analysis showed that common diagnostics like the twice-mean and thrice-mean rules failed to detect HLP in the given data set whilst robust approaches such as the potentials and diagnostic-robust generalized potentials (DRGP) methods were found to be successful in identifying high leverage point as indicated by lower values of the Pearson s correlation coefficient and variance inflation factors. |
| first_indexed | 2025-11-14T21:36:02Z |
| format | Article |
| id | uitm-13085 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:36:02Z |
| publishDate | 2010 |
| publisher | Research Management Institute (RMI) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-130852023-04-10T07:21:02Z https://ir.uitm.edu.my/id/eprint/13085/ Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] smrj Mohamed Ramli, Norazan Mahmud, Zamalia Zakaria, Husein Idris, Mohammad Radzi Abdul Aziz, Alizan Managerial accounting Balance sheet. Financial statements. Corporation reports. Including pro forma statements Inaccurate and invalid statistical inferences in regression analysis may be caused by multicollinearity due to the presence of high leverage points (HLP) in a data set. Therefore, it is important that high leverage point which is a form ofoutlier be detected because its existence can lead to misfitting of a regression model, thus resulting in inaccuracy of regression results. In this paper, several methods have been proposed to identify HLP in a financial accounting data set prior to conducting further analysis of regression and other multivariate analysis. The Pearson scorrelation coefficient and variance inflation factors (VIF) were used to measure the success of a detection method. Numerical analysis showed that common diagnostics like the twice-mean and thrice-mean rules failed to detect HLP in the given data set whilst robust approaches such as the potentials and diagnostic-robust generalized potentials (DRGP) methods were found to be successful in identifying high leverage point as indicated by lower values of the Pearson s correlation coefficient and variance inflation factors. Research Management Institute (RMI) 2010 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/13085/2/13085.pdf Mohamed Ramli, Norazan and Mahmud, Zamalia and Zakaria, Husein and Idris, Mohammad Radzi and Abdul Aziz, Alizan (2010) Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.]. (2010) Social and Management Research Journal (SMRJ) <https://ir.uitm.edu.my/view/publication/Social_and_Management_Research_Journal_=28SMRJ=29.html>, 7 (2). pp. 17-30. ISSN 1675-7017 https://smrj.uitm.edu.my/ |
| spellingShingle | Managerial accounting Balance sheet. Financial statements. Corporation reports. Including pro forma statements Mohamed Ramli, Norazan Mahmud, Zamalia Zakaria, Husein Idris, Mohammad Radzi Abdul Aziz, Alizan Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title | Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title_full | Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title_fullStr | Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title_full_unstemmed | Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title_short | Assessing multicollinearity via identification of high leverage points in financial accounting data / Norazan Mohamed Ramli ... [et al.] |
| title_sort | assessing multicollinearity via identification of high leverage points in financial accounting data / norazan mohamed ramli ... [et al.] |
| topic | Managerial accounting Balance sheet. Financial statements. Corporation reports. Including pro forma statements |
| url | https://ir.uitm.edu.my/id/eprint/13085/ https://ir.uitm.edu.my/id/eprint/13085/ |