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Headrick, Todd C.; Sawilowsky, Shlomo S. – 2000
Real world data often fail to meet the underlying assumption of population normality. The Rank Transformation (RT) procedure has been recommended as an alternative to the parametric factorial analysis of Covariance (ANCOVA). The purpose of this study was to compare the Type I error and power properties of the RT ANCOVA to the parametric procedures…
Descriptors: Analysis of Covariance, Factor Analysis, Factor Structure, Nonparametric Statistics
Fahoome, Gail; Sawilowsky, Shlomo S. – 2000
Nonparametric procedures are often more powerful than classical tests for real world data, which are rarely normally distributed. However, there are difficulties in using these tests. Computational formulas are scattered throughout the literature, and there is a lack of availability of tables of critical values. This paper brings together the…
Descriptors: Monte Carlo Methods, Nonparametric Statistics, Sample Size, Statistical Distributions
Fan, Xitao – 2001
Bootstrap analysis, both for nonparametric statistical inference and for describing sample results stability and replicability, has been gaining prominence among quantitative researchers in educational and psychological research. Procedurally, however, it is often quite a challenge for quantitative researchers to implement bootstrap analysis in…
Descriptors: Computer Software, Educational Research, Heuristics, Nonparametric Statistics
Hanson, Bradley A.; Bay, Luz; Loomis, Susan Cooper – 1998
Research studies using booklet classification were implemented by the American College Testing Program to investigate the linkage between the National Assessment of Educational Progress (NAEP) Achievement Levels Descriptions and the cutpoints set to represent student performance with respect to the achievement levels. This paper describes the…
Descriptors: Academic Achievement, Classification, Cutting Scores, Discriminant Analysis