{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T03:28:47Z","timestamp":1771903727819,"version":"3.50.1"},"reference-count":9,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["KES"],"published-print":{"date-parts":[[2023,7,13]]},"abstract":"<jats:p>Multicollinearity occurs when there comes a high level of correlation between the independent variables. This correlation creates the problem because the independent variables should be independent. Higher the degree of correlation means more complex problems you will face while fitting the model and interpreting the results. In this paper, we have eliminated the problem of multicollinearity on the basis of Hatvalues. The variables with higher Hatvalues will be removed from the data before fitting the model. This paper presents the comparison of results achieved by the proposed technique and state of the art methods.<\/jats:p>","DOI":"10.3233\/kes-221622","type":"journal-article","created":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T15:22:24Z","timestamp":1688138544000},"page":"105-111","source":"Crossref","is-referenced-by-count":4,"title":["Detection and elimination of multicollinearity in regression analysis"],"prefix":"10.1177","volume":"27","author":[{"given":"Preeti","family":"Singh","sequence":"first","affiliation":[]},{"given":"Sarvpal","family":"Singh","sequence":"additional","affiliation":[]},{"given":"Marcin","family":"Paprzycki","sequence":"additional","affiliation":[]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/KES-221622_ref1","doi-asserted-by":"crossref","first-page":"2576","DOI":"10.1080\/03610918.2015.1053925","article-title":"Some new methods to solve multicollinearity in logistic regression","volume":"46","author":"Asar","year":"2015","journal-title":"Communications in Statistics \u2013 Simulation and Computation."},{"key":"10.3233\/KES-221622_ref2","unstructured":"Bager A, Roman M, Algedih M, et al. Addressing multicollinearity in regression models: a ridge regression application, 2017."},{"key":"10.3233\/KES-221622_ref3","unstructured":"Chatterjee S, Hadi AS. Regression Analysis by Example. John Wiley & Sons, 2015."},{"key":"10.3233\/KES-221622_ref4","doi-asserted-by":"crossref","unstructured":"Duzan H. Solution to the Multicollinearity Problem by Adding some Constant to the Diagonal. Journal of Modern Applied Statistical Methods. 2016; 15(1).","DOI":"10.22237\/jmasm\/1462077360"},{"key":"10.3233\/KES-221622_ref5","first-page":"48","article-title":"Principles of Regression Analysis","volume":"65","author":"Gogtay","year":"2017","journal-title":"Journal of The Association of Physicians of India."},{"issue":"8","key":"10.3233\/KES-221622_ref6","doi-asserted-by":"crossref","first-page":"2362","DOI":"10.1002\/smj.2783","article-title":"Multicollinearity: How common factors cause Type 1 errors in multivariate regression","volume":"39","author":"Kalnins","year":"2018","journal-title":"Strategic Management Journal."},{"key":"10.3233\/KES-221622_ref7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eswa.2017.01.048","article-title":"Comprehensive study of feature selection methods to solve multicollinearity problem according to evaluation criteria","volume":"76","author":"Katrutsa","year":"2017","journal-title":"Expert Systems with Applications."},{"key":"10.3233\/KES-221622_ref8","first-page":"647","article-title":"Diagnosis and quantification of the non-essential collinearity","volume":"35","author":"Rodr\u00edguez-S\u00e1nchez","year":"2019","journal-title":"Computational Statistics."},{"key":"10.3233\/KES-221622_ref9","doi-asserted-by":"crossref","unstructured":"Saeed N, Haewoon Nam MI. A Survey on Multidimensional Scaling. ACM Computing Surveys. 2018 May; 51(3).","DOI":"10.1145\/3178155"}],"container-title":["International Journal of Knowledge-based and Intelligent Engineering Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/KES-221622","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T17:09:28Z","timestamp":1741626568000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/KES-221622"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,13]]},"references-count":9,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/kes-221622","relation":{},"ISSN":["1327-2314","1875-8827"],"issn-type":[{"value":"1327-2314","type":"print"},{"value":"1875-8827","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,13]]}}}