Power of Pairwise Multiple Comparisons in the Unequal Variance Case [electronic resource] / Tung-Hsing Hsiung and Stephen Olejnik.
Using computer simulated data, the Type I error rate and statistical power were empirically estimated for several pairwise multiple comparison strategies for situations where population variances differ. Focus was on comparing modified Bonferroni procedures with Dunnett's solutions, and determi...
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| Format: | Electronic eBook |
| Language: | English |
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Distributed by ERIC Clearinghouse,
1991.
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MARC
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| 100 | 1 | |a Hsiung, Tung-Hsing. | |
| 245 | 1 | 0 | |a Power of Pairwise Multiple Comparisons in the Unequal Variance Case |h [electronic resource] / |c Tung-Hsing Hsiung and Stephen Olejnik. |
| 260 | |a [S.l.] : |b Distributed by ERIC Clearinghouse, |c 1991. | ||
| 300 | |a 34 p. | ||
| 500 | |a ERIC Document Number: ED334213. | ||
| 500 | |a ERIC Note: Paper presented at the Annual Meeting of the American Educational Research Association (Chicago, IL, April 3-7, 1991). |5 ericd. | ||
| 520 | |a Using computer simulated data, the Type I error rate and statistical power were empirically estimated for several pairwise multiple comparison strategies for situations where population variances differ. Focus was on comparing modified Bonferroni procedures with Dunnett's solutions, and determining whether or not J. P. Shaffer's suggestion of using the omnibus test would work when population variances differed. Three factors were manipulated: sample size, variance heterogeneity, and pattern of population mean differences. Twenty-four different combinations of sample sizes and variance patterns were examined for the single factor four group design. The results indicate that all eight contrast procedures considered controlled the familywise Type I error rate under the nominal 0.05 level. In terms of statistical power, the Games-Howell procedure generally provided the greater power in identifying at least one significant difference. However, the magnitude of the any-pair power difference was very small. J. P. Shaffer's (1979) enhancements to the Bonferroni approach provided greater average power per contrast as well as the greatest power in identifying all significant pairwise differences. The results of the present study indicate that previous recommendations concerning the selection of a multiple comparison procedure when population variances differ should be reconsidered, and the adoption of the new strategies for multiple comparisons is recommended. Twelve data tables and a 22-item list of references are included. (Author/RLC) | ||
| 650 | 1 | 7 | |a Comparative Analysis. |2 ericd. |
| 650 | 0 | 7 | |a Equations (Mathematics) |2 ericd. |
| 650 | 1 | 7 | |a Estimation (Mathematics) |2 ericd. |
| 650 | 1 | 7 | |a Mathematical Models. |2 ericd. |
| 650 | 0 | 7 | |a Power (Statistics) |2 ericd. |
| 650 | 0 | 7 | |a Sample Size. |2 ericd. |
| 650 | 0 | 7 | |a Simulation. |2 ericd. |
| 700 | 1 | |a Olejnik, Stephen. | |
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