Sains Malaysiana 48(9)(2019): 2051–2060
http://dx.doi.org/10.17576/jsm-2019-4809-26
Some New Diagnostics of
Multicollinearity in Linear Regression Model
(Beberapa Diagnostik
Baru Multikekolinearan dalam Model Regresi Linear)
MUHAMMAD IMDAD ULLAH1*, MUHAMMAD ASLAM1, SAIMA ALTAF1 & MUNIR AHMED2
1Department
of Statistics, Bahauddin Zakariya University, Multan 60800, Pakistan
2Department
of Management Sciences, COMSAT University, Vehari Campus, Islamabad
Diserahkan:
21 Oktober 2018/Diterima: 3 Mei 2019
ABSTRACT
The problem of
multicollinearity compromises the numerical stability of the regression
coefficient estimate and cause some serious problem in validation and
interpretation of the model. In this paper, we propose two new collinearity
diagnostics for the detection of collinearity among regressors, based on
coefficient of determination and adjusted coefficient of determination from
auxiliary regression of regressors. A Monte Carlo simulation study has been
conducted to compare the existing and proposed collinearity diagnostic tests.
Comparison of diagnostics on some existing collinear data are also made.
Keywords: Collinearity
diagnostics; ill-conditioning; linear dependencies; multicollinearity;
regression analysis
ABSTRAK
Masalah multikekolinearan
kompromi kestabilan berangka pekali regresi anggaran dan menyebabkan beberapa
masalah serius dalam pengesahan dan tafsiran model. Dalam kajian ini, kami
mencadangkan dua diagnostik kekolinearan baru untuk pengesanan kekolinearan
dalam kalangan peregrasi, berdasarkan pekali penentuan dan pekali penentuan
terlaras daripada bantuan regresi oleh peregrasi. Kajian simulasi Monte Carlo
telah dijalankan untuk membandingkan kajian kekolinearan sedia ada dengan
cadangan ujian kekolinearan diagnostik. Perbandingan diagnostik pada sesetengah
data kolinear sedia ada turut dijalankan.
Kata kunci: Analisis
regresi; kebergantungan linear; kekolinearan diagnostik; multi-kekolinearan;
persuasanaan tak sihat
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*Pengarang untuk surat-menyurat;
email: mimdadasad@gmail.com
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