A Review of Nonparametric Alternatives to Analysis of Covariance [electronic resource] / Stephen F. Olejnik and James Algina.
Five distribution-free alternatives to parametric analysis of covariance (ANCOVA) are presented and demonstrated using a specific data example. The procedures considered are those suggested by Quade (1967); Puri and Sen (1969); McSweeney and Porter (1971); Burnett and Barr (1978); and Shirley (1981)...
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| Format: | Electronic eBook |
| Language: | English |
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[S.l.] :
Distributed by ERIC Clearinghouse,
1984.
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MARC
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| 100 | 1 | |a Olejnik, Stephen F. | |
| 245 | 1 | 2 | |a A Review of Nonparametric Alternatives to Analysis of Covariance |h [electronic resource] / |c Stephen F. Olejnik and James Algina. |
| 260 | |a [S.l.] : |b Distributed by ERIC Clearinghouse, |c 1984. | ||
| 300 | |a 46 p. | ||
| 500 | |a ERIC Document Number: ED246063. | ||
| 500 | |a ERIC Note: Paper presented at the Annual Meeting of the American Educational Research Association (68th, New Orleans, LA, April 23-27, 1984). |5 ericd. | ||
| 520 | |a Five distribution-free alternatives to parametric analysis of covariance (ANCOVA) are presented and demonstrated using a specific data example. The procedures considered are those suggested by Quade (1967); Puri and Sen (1969); McSweeney and Porter (1971); Burnett and Barr (1978); and Shirley (1981). The results of simulation studies investigating these procedures regarding their respective Type I error rate under a null condition and their statistical power are also reviewed. The results indicate that the nonparametric procedures have appropriate Type I error rates only for those situations in which parametric ANCOVA is robust to violations of data assumptions. In terms of statistical power, nonparametric alternatives to parametric ANCOVA provide a considerable power advantage only for situations where extreme violations of assumptions have occurred and the linear relationship between measures is weak. (Author/DWH) | ||
| 521 | 8 | |a Researchers. |b ericd. | |
| 650 | 1 | 7 | |a Analysis of Covariance. |2 ericd. |
| 650 | 0 | 7 | |a Comparative Analysis. |2 ericd. |
| 650 | 0 | 7 | |a Hypothesis Testing. |2 ericd. |
| 650 | 1 | 7 | |a Mathematical Formulas. |2 ericd. |
| 650 | 1 | 7 | |a Nonparametric Statistics. |2 ericd. |
| 650 | 1 | 7 | |a Power (Statistics) |2 ericd. |
| 650 | 0 | 7 | |a Regression (Statistics) |2 ericd. |
| 650 | 0 | 7 | |a Statistical Distributions. |2 ericd. |
| 700 | 1 | |a Algina, James. | |
| 856 | 4 | 0 | |u http://files.eric.ed.gov/fulltext/ED246063.pdf |z Full Text (via ERIC) |
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