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| Autor/in | Thompson, Bruce |
|---|---|
| Titel | Exploring the Replicability of a Study's Results: Bootstrap Statistics for the Multivariate Case. |
| Quelle | (1992), (40 Seiten)
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Analysis of Covariance; Analysis of Variance; Correlation; Discriminant Analysis; Multivariate Analysis; Regression (Statistics); Research Methodology; Sampling; Statistical Significance |
| Abstract | Conventional statistical significance tests do not inform the researcher regarding the likelihood that results will replicate. One strategy for evaluating result replication is to use a "bootstrap" resampling of a study's data so that the stability of results across numerous configurations of the subjects can be explored. This paper illustrates the use of the bootstrap in a canonical correlation analysis. Canonical correlation analysis is the most general case of classical general linear model analyses, subsuming other univariate and multivariate parametric method (e.g., t-tests, analysis of variance, analysis of covariance, regression, multivariate analysis of variance, and discriminant analysis) as special cases. A sample of 50 out of 301 subjects from a study by K. J. Holzinger and F. Swineford (1939) is used. Since bootstrap analyses capitalize during resampling on the commonalities inherent in a given sample, they yield somewhat inflated evaluations of replicability. However, inflated empirical evaluations of replicability are often superior to a mere presumption of replicability. Ten tables and one figure present details of the analysis. A 63-item list of references and an appendix listing the 50 analysis cases are included. (Author/SLD) |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
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