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ERIC Number: EJ782681
Record Type: Journal
Publication Date: 2007-Dec
Pages: 20
Abstractor: Author
Reference Count: 0
ISSN: ISSN-1082-989X
Bootstrapping to Test for Nonzero Population Correlation Coefficients Using Univariate Sampling
Beasley, William Howard; DeShea, Lise; Toothaker, Larry E.; Mendoza, Jorge L.; Bard, David E.; Rodgers, Joseph Lee
Psychological Methods, v12 n4 p414-433 Dec 2007
This article proposes 2 new approaches to test a nonzero population correlation ([rho]): the hypothesis-imposed univariate sampling bootstrap (HI) and the observed-imposed univariate sampling bootstrap (OI). The authors simulated correlated populations with various combinations of normal and skewed variates. With [alpha[subscript "set"]]=0.05, N greater than or equal to 10, and [rho] greater than or equal to 0.4, empirical Type I error rates of the parametric r and the conventional bivariate sampling bootstrap reached 0.168 and 0.081, respectively, whereas the largest error rates of the HI and the OI were 0.079 and 0.062. On the basis of these results, the authors suggest that the OI is preferable in alpha control to parametric approaches if the researcher believes the population is nonnormal and wishes to test for nonzero [rho]s of moderate size.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A