PDF pending restoration
ERIC Number: ED246063
Record Type: RIE
Publication Date: 1984-Apr
Reference Count: 0
A Review of Nonparametric Alternatives to Analysis of Covariance.
Olejnik, Stephen F.; Algina, James
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)
Publication Type: Speeches/Meeting Papers; Reports - Research; Information Analyses
Education Level: N/A
Authoring Institution: N/A
Identifiers: Type I Errors; Violation of Assumptions
Note: Paper presented at the Annual Meeting of the American Educational Research Association (68th, New Orleans, LA, April 23-27, 1984).