Comparison of the performances of parametric k-sample test procedures as an alternative to one-way analysis of variance
Objectives: The performances of the Welch test, the Alexander-Govern test, the Brown-Forsythe test and the James Second-Order test, which are among the parametric alternatives of one-way analysis of variance and included in the literature, to protect the Type-I error probability determined at the be...
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Veröffentlicht in: | The European research journal 2023-01, Vol.9 (1), p.39-48 |
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description | Objectives: The performances of the Welch test, the Alexander-Govern test, the Brown-Forsythe test and the James Second-Order test, which are among the parametric alternatives of one-way analysis of variance and included in the literature, to protect the Type-I error probability determined at the beginning of the trial at a nominal level, were compared with the F test.
Methods: Performance of the tests to protect Type-I error; in cases where the variances are homogeneous and heterogeneous, the sample sizes are balanced and unbalanced, the distribution of the data is in accordance with the normal distribution and the log-normal distribution, how it is affected by the change in the number of groups to be compared has been examined on simulation scenarios.
Results: The Welch test, the Alexander-Govern test and the James Second-Order test were not affected by the distribution and performed well in situations where variances were heterogeneous. The Brown-Forsythe test was not affected by the distribution, it performed well when the variance was homogeneous and the sample size in the groups to be compared was not equal.
Conclusions: The Welch test, the Alexander-Govern test and the James Second-Order test are the tests that can be recommended as an alternative to the F test. |
doi_str_mv | 10.18621/eurj.1030038 |
format | Article |
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Methods: Performance of the tests to protect Type-I error; in cases where the variances are homogeneous and heterogeneous, the sample sizes are balanced and unbalanced, the distribution of the data is in accordance with the normal distribution and the log-normal distribution, how it is affected by the change in the number of groups to be compared has been examined on simulation scenarios.
Results: The Welch test, the Alexander-Govern test and the James Second-Order test were not affected by the distribution and performed well in situations where variances were heterogeneous. The Brown-Forsythe test was not affected by the distribution, it performed well when the variance was homogeneous and the sample size in the groups to be compared was not equal.
Conclusions: The Welch test, the Alexander-Govern test and the James Second-Order test are the tests that can be recommended as an alternative to the F test.</description><identifier>ISSN: 2149-3189</identifier><identifier>EISSN: 2149-3189</identifier><identifier>DOI: 10.18621/eurj.1030038</identifier><language>eng</language><ispartof>The European research journal, 2023-01, Vol.9 (1), p.39-48</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c778-59b51809256c56d8bbe8c54a7a10d9e6058ea570569183eda50444a250fb66f93</cites><orcidid>0000-0002-6802-5998 ; 0000-0002-1114-6051</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,27929,27930</link.rule.ids></links><search><creatorcontrib>OCAKOĞLU, Gökhan</creatorcontrib><creatorcontrib>MACUNLUOGLU, Aslı Ceren</creatorcontrib><title>Comparison of the performances of parametric k-sample test procedures as an alternative to one-way analysis of variance</title><title>The European research journal</title><description>Objectives: The performances of the Welch test, the Alexander-Govern test, the Brown-Forsythe test and the James Second-Order test, which are among the parametric alternatives of one-way analysis of variance and included in the literature, to protect the Type-I error probability determined at the beginning of the trial at a nominal level, were compared with the F test.
Methods: Performance of the tests to protect Type-I error; in cases where the variances are homogeneous and heterogeneous, the sample sizes are balanced and unbalanced, the distribution of the data is in accordance with the normal distribution and the log-normal distribution, how it is affected by the change in the number of groups to be compared has been examined on simulation scenarios.
Results: The Welch test, the Alexander-Govern test and the James Second-Order test were not affected by the distribution and performed well in situations where variances were heterogeneous. The Brown-Forsythe test was not affected by the distribution, it performed well when the variance was homogeneous and the sample size in the groups to be compared was not equal.
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Methods: Performance of the tests to protect Type-I error; in cases where the variances are homogeneous and heterogeneous, the sample sizes are balanced and unbalanced, the distribution of the data is in accordance with the normal distribution and the log-normal distribution, how it is affected by the change in the number of groups to be compared has been examined on simulation scenarios.
Results: The Welch test, the Alexander-Govern test and the James Second-Order test were not affected by the distribution and performed well in situations where variances were heterogeneous. The Brown-Forsythe test was not affected by the distribution, it performed well when the variance was homogeneous and the sample size in the groups to be compared was not equal.
Conclusions: The Welch test, the Alexander-Govern test and the James Second-Order test are the tests that can be recommended as an alternative to the F test.</abstract><doi>10.18621/eurj.1030038</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-6802-5998</orcidid><orcidid>https://orcid.org/0000-0002-1114-6051</orcidid><oa>free_for_read</oa></addata></record> |
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title | Comparison of the performances of parametric k-sample test procedures as an alternative to one-way analysis of variance |
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