Score Test for Homogeneity of Variances in Normal Distributions.
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| Title: | Score Test for Homogeneity of Variances in Normal Distributions. |
|---|---|
| Authors: | AKSOY, Sevgi1, GOKPINAR, Fikri2, GOKPINAR, Esra2 eyigit@gazi.edu.tr |
| Source: | Gazi University Journal of Science. 2025, Vol. 38 Issue 3, p1503-1516. 14p. |
| Subjects: | Homoscedasticity, Statistical hypothesis testing, Simulation methods & models, Mathematical statistics, Chi-squared test, Gaussian distribution, Resampling (Statistics) |
| Abstract: | In this study, we suggest a novel test statistic based on the Score statistic for evaluating the homogeneity of variances in normal distributions. In addition to the conventional chi-square approximation of the Score statistic, we introduce a parametric bootstrap technique known as the Computational Approach Test (CAT). Through a simulation study, we evaluate the proposed test's CAT approach (referred to as CS) and assess its performance against established methods under varying group sizes and sample sizes. The results show that, regardless of the number of groups, the CAT approach of the Score test performs well when sample sizes and variances are directly proportional, even with a minimum sample size of three. Furthermore, when sample sizes and variances are inversely proportional, the proposed test significantly outperforms alternative methods. To demonstrate the application of the discussed methods, we provide two numerical examples. [ABSTRACT FROM AUTHOR] |
| Copyright of Gazi University Journal of Science is the property of Gazi University Journal of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 188786855 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Score Test for Homogeneity of Variances in Normal Distributions. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22AKSOY%2C+Sevgi%22">AKSOY, Sevgi</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22GOKPINAR%2C+Fikri%22">GOKPINAR, Fikri</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22GOKPINAR%2C+Esra%22">GOKPINAR, Esra</searchLink><relatesTo>2</relatesTo><i> eyigit@gazi.edu.tr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Gazi+University+Journal+of+Science%22">Gazi University Journal of Science</searchLink>. 2025, Vol. 38 Issue 3, p1503-1516. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Homoscedasticity%22">Homoscedasticity</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+hypothesis+testing%22">Statistical hypothesis testing</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+statistics%22">Mathematical statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Gaussian+distribution%22">Gaussian distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Resampling+%28Statistics%29%22">Resampling (Statistics)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this study, we suggest a novel test statistic based on the Score statistic for evaluating the homogeneity of variances in normal distributions. In addition to the conventional chi-square approximation of the Score statistic, we introduce a parametric bootstrap technique known as the Computational Approach Test (CAT). Through a simulation study, we evaluate the proposed test's CAT approach (referred to as CS) and assess its performance against established methods under varying group sizes and sample sizes. The results show that, regardless of the number of groups, the CAT approach of the Score test performs well when sample sizes and variances are directly proportional, even with a minimum sample size of three. Furthermore, when sample sizes and variances are inversely proportional, the proposed test significantly outperforms alternative methods. To demonstrate the application of the discussed methods, we provide two numerical examples. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Gazi University Journal of Science is the property of Gazi University Journal of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.35378/gujs.1604187 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1503 Subjects: – SubjectFull: Homoscedasticity Type: general – SubjectFull: Statistical hypothesis testing Type: general – SubjectFull: Simulation methods & models Type: general – SubjectFull: Mathematical statistics Type: general – SubjectFull: Chi-squared test Type: general – SubjectFull: Gaussian distribution Type: general – SubjectFull: Resampling (Statistics) Type: general Titles: – TitleFull: Score Test for Homogeneity of Variances in Normal Distributions. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: AKSOY, Sevgi – PersonEntity: Name: NameFull: GOKPINAR, Fikri – PersonEntity: Name: NameFull: GOKPINAR, Esra IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13039709 Numbering: – Type: volume Value: 38 – Type: issue Value: 3 Titles: – TitleFull: Gazi University Journal of Science Type: main |
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