A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern

Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In...

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Main Authors:	Habshah Midi, Bagheri, Arezoo, Rahmatulllah Imon .A.H.M
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2011
Online Access:	http://journalarticle.ukm.my/3145/ http://journalarticle.ukm.my/3145/ http://journalarticle.ukm.my/3145/1/14_Habshah_Midi.pdf

id	ukm-3145
recordtype	eprints
spelling	ukm-31452016-12-14T06:33:44Z http://journalarticle.ukm.my/3145/ A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern Habshah Midi, Bagheri, Arezoo Rahmatulllah Imon .A.H.M, Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In this paper, we performed Monte Carlo simulation studies to achieve two main objectives. The first objective was to study the effect of certain magnitude and percentage of high leverage points, which are two important issues in tending the high leverage points to be collinearity-enhancing observations, on the multicollinarity pattern of the data. The second objective was to investigate in which situations these points do make different degrees of multicollinearity, such as moderate or severe. According to the simulation results, high leverage points should be in large magnitude for at least two explanatory variables to guarantee that they are the cause of multicollinearity problems. We also proposed some practical Lower Bound (LB) and Upper Bound (UB) for High Leverage Collinearity Influential Measure (HLCIM) which is an essential measure in detecting the degree of multicollinearity. A well-known example is used to confirm the simulation results. Universiti Kebangsaan Malaysia 2011-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/3145/1/14_Habshah_Midi.pdf Habshah Midi, and Bagheri, Arezoo and Rahmatulllah Imon .A.H.M, (2011) A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern. Sains Malaysiana, 40 (12). pp. 1437-1447. ISSN 0126-6039 http://www.ukm.my/jsm/
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In this paper, we performed Monte Carlo simulation studies to achieve two main objectives. The first objective was to study the effect of certain magnitude and percentage of high leverage points, which are two important issues in tending the high leverage points to be collinearity-enhancing observations, on the multicollinarity pattern of the data. The second objective was to investigate in which situations these points do make different degrees of multicollinearity, such as moderate or severe. According to the simulation results, high leverage points should be in large magnitude for at least two explanatory variables to guarantee that they are the cause of multicollinearity problems. We also proposed some practical Lower Bound (LB) and Upper Bound (UB) for High Leverage Collinearity Influential Measure (HLCIM) which is an essential measure in detecting the degree of multicollinearity. A well-known example is used to confirm the simulation results.
format	Article
author	Habshah Midi, Bagheri, Arezoo Rahmatulllah Imon .A.H.M,
spellingShingle	Habshah Midi, Bagheri, Arezoo Rahmatulllah Imon .A.H.M, A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
author_facet	Habshah Midi, Bagheri, Arezoo Rahmatulllah Imon .A.H.M,
author_sort	Habshah Midi,
title	A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
title_short	A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
title_full	A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
title_fullStr	A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
title_full_unstemmed	A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
title_sort	monte carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
publisher	Universiti Kebangsaan Malaysia
publishDate	2011
url	http://journalarticle.ukm.my/3145/ http://journalarticle.ukm.my/3145/ http://journalarticle.ukm.my/3145/1/14_Habshah_Midi.pdf
first_indexed	2023-09-18T19:38:00Z
last_indexed	2023-09-18T19:38:00Z
_version_	1777405400336826368

A Monte Carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern

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