Examining the impact of Sample and Effect Sizes on the Power of One-way Analysis of Variance F-test.
| dc.contributor.author | Oyeyemi, G. M. | |
| dc.contributor.author | Adeleke, B. L. | |
| dc.date.accessioned | 2023-07-19T09:39:40Z | |
| dc.date.available | 2023-07-19T09:39:40Z | |
| dc.date.issued | 2012 | |
| dc.description.abstract | The power of a test is a function of three factors; sample size, the size of detectable effects and the level of significance. The paper focused on determining the non-centrality parameter in one-way analysis of variance (ANOVA) test which by implication utilizes the completely randomized design. To examine the contributing effect of sample size and size of detectable effects, data were simulated for varying levels of treatments, replicates and effect sizes for several experiments of the completely randomized design type. The results showed that power of the F test increased monotonically with size of non-centrality parameter λ, where non-centrality parameter is a function effect size. An increase in sample size also brings proportionate increases in power irrespective of the number of treatments under consideration. | en_US |
| dc.description.sponsorship | Self-sponsored | en_US |
| dc.identifier.citation | International Journal Statistics and System | en_US |
| dc.identifier.issn | 0973-2675 | |
| dc.identifier.uri | https://uilspace.unilorin.edu.ng/handle/20.500.12484/11563 | |
| dc.language.iso | en | en_US |
| dc.publisher | Research India Publications | en_US |
| dc.relation.ispartofseries | 7(2);101 - 108 | |
| dc.subject | Non-centrality parameter, Power, Effect size, Replicate Treatment | en_US |
| dc.title | Examining the impact of Sample and Effect Sizes on the Power of One-way Analysis of Variance F-test. | en_US |
| dc.type | Article | en_US |