A Priori Versus Post-Hoc: Comparing Statistical Power among ANOVA, Block Designs, and ANCOVA.
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| Title: | A Priori Versus Post-Hoc: Comparing Statistical Power among ANOVA, Block Designs, and ANCOVA. |
|---|---|
| Language: | English |
| Authors: | Wu, Yi-Cheng, McLean, James E. |
| Peer Reviewed: | N |
| Page Count: | 28 |
| Publication Date: | 1994 |
| Document Type: | Reports - Evaluative Speeches/Meeting Papers |
| Descriptors: | Analysis of Covariance, Analysis of Variance, Comparative Analysis, Power (Statistics), Research Design, Research Methodology |
| Assessment and Survey Identifiers: | Block Design Test |
| Abstract: | By employing a concomitant variable, block designs and analysis of covariance (ANCOVA) can be used to improve the power of traditional analysis of variance (ANOVA) by reducing error. If subjects are randomly assigned to treatments without considering the concomitant variable, an experiment uses a post-hoc approach. Otherwise, an a priori approach is used if the concomitant variable is utilized for assigning subjects to treatments. Traditionally, a priori has been considered the more powerful approach. This study compared ANOVA, block designs, and ANCOVA under various experimental conditions. The experimental conditions were 48 combinations of 4 levels of the number of treatments (T at 2, 3, 4, and 5), 3 levels of the number of subjects per treatment (n at 8, 40, and 72), and 4 levels of the correlation coefficient between the concomitant and dependent variables (p at 0.00, 0.28, 0.56, and 0.84). The optimal number of blocks to achieve maximum power was also investigated. Results indicated that a priori was not generally more powerful than post-hoc. For ANOVA, a priori became less powerful as T and p increased. For block designs, the preference depended on the experimental conditions. For ANCOVA, a priori was more powerful when T and n were small. Appendix A explores apparent imprecision, Appendix B presents two Statistical Analysis System computer programs, and Appendix C contains a power table. (Contains 9 tables and 3 references.) (Author/SLD) |
| Entry Date: | 1996 |
| Accession Number: | ED387531 |
| Database: | ERIC |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED387531 Name: ERIC Full Text Category: fullText Text: Full Text from ERIC |
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| Header | DbId: eric DbLabel: ERIC An: ED387531 AccessLevel: 3 PubType: Report PubTypeId: report PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Priori Versus Post-Hoc: Comparing Statistical Power among ANOVA, Block Designs, and ANCOVA. – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wu%2C+Yi-Cheng%22">Wu, Yi-Cheng</searchLink><br /><searchLink fieldCode="AR" term="%22McLean%2C+James+E%2E%22">McLean, James E.</searchLink> – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: N – Name: Pages Label: Page Count Group: Src Data: 28 – Name: DatePubCY Label: Publication Date Group: Date Data: 1994 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Reports - Evaluative<br />Speeches/Meeting Papers – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Analysis+of+Covariance%22">Analysis of Covariance</searchLink><br /><searchLink fieldCode="DE" term="%22Analysis+of+Variance%22">Analysis of Variance</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+Analysis%22">Comparative Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Power+%28Statistics%29%22">Power (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Design%22">Research Design</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Methodology%22">Research Methodology</searchLink> – Name: SubjectThesaurus Label: Assessment and Survey Identifiers Group: Su Data: <searchLink fieldCode="SU" term="%22Block+Design+Test%22">Block Design Test</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: By employing a concomitant variable, block designs and analysis of covariance (ANCOVA) can be used to improve the power of traditional analysis of variance (ANOVA) by reducing error. If subjects are randomly assigned to treatments without considering the concomitant variable, an experiment uses a post-hoc approach. Otherwise, an a priori approach is used if the concomitant variable is utilized for assigning subjects to treatments. Traditionally, a priori has been considered the more powerful approach. This study compared ANOVA, block designs, and ANCOVA under various experimental conditions. The experimental conditions were 48 combinations of 4 levels of the number of treatments (T at 2, 3, 4, and 5), 3 levels of the number of subjects per treatment (n at 8, 40, and 72), and 4 levels of the correlation coefficient between the concomitant and dependent variables (p at 0.00, 0.28, 0.56, and 0.84). The optimal number of blocks to achieve maximum power was also investigated. Results indicated that a priori was not generally more powerful than post-hoc. For ANOVA, a priori became less powerful as T and p increased. For block designs, the preference depended on the experimental conditions. For ANCOVA, a priori was more powerful when T and n were small. Appendix A explores apparent imprecision, Appendix B presents two Statistical Analysis System computer programs, and Appendix C contains a power table. (Contains 9 tables and 3 references.) (Author/SLD) – Name: DateEntry Label: Entry Date Group: Date Data: 1996 – Name: AN Label: Accession Number Group: ID Data: ED387531 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED387531 |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 28 Subjects: – SubjectFull: Analysis of Covariance Type: general – SubjectFull: Analysis of Variance Type: general – SubjectFull: Comparative Analysis Type: general – SubjectFull: Power (Statistics) Type: general – SubjectFull: Research Design Type: general – SubjectFull: Research Methodology Type: general – SubjectFull: Block Design Test Type: general Titles: – TitleFull: A Priori Versus Post-Hoc: Comparing Statistical Power among ANOVA, Block Designs, and ANCOVA. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wu, Yi-Cheng – PersonEntity: Name: NameFull: McLean, James E. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Type: published Y: 1994 |
| ResultId | 1 |
