The Highly Gifted: definitions and methodological implications
- 1 June 1998
- journal article
- research article
- Published by Taylor & Francis in High Ability Studies
- Vol. 9 (1) , 23-41
- https://doi.org/10.1080/1359813980090103
Abstract
This paper is concerned with the methodological implications of various definitions of the term ‘highly gifted’. Three definitions of ‘highly gifted’ are presented. It is shown that the definition of the term ‘highly gifted’ has considerable methodological implications. These implications concern both choice of method for data analysis and results of analysis. Conditions for proper application of standard statistical methods including the t‐test for mean difference, the F‐test for regression slope differences, MANOVA, and discriminant analysis are reviewed. It is also shown that, under circumstances that are far from unrealistic, there are no methods with known properties available for data analysis.Keywords
This publication has 15 references indexed in Scilit:
- Alternative procedures for testing regression slope homogeneity when group error variances are unequal.Psychological Methods, 1996
- Identifying Young, Potentially Gifted, Economically Disadvantaged Students1Gifted Child Quarterly, 1994
- Effect of error variance heterogeneity on the power of tests for regression slope differences.Psychological Bulletin, 1994
- A New and Simpler Approximation for ANOVA under Variance HeterogeneityJournal of Educational Statistics, 1994
- A Connection Between the Logit Model, Normal Discriminant Analysis, and Multivariate Normal MixturesThe American Statistician, 1991
- Variable Selection to Discriminate Between Two Groups: Stepwise Logistic Regression or Stepwise Discriminant Analysis?The American Statistician, 1991
- 7 Robustness of ANOVA and MANOVA test proceduresPublished by Elsevier ,1980
- Choosing Between Logistic Regression and Discriminant AnalysisJournal of the American Statistical Association, 1978
- The Efficiency of Logistic Regression Compared to Normal Discriminant AnalysisJournal of the American Statistical Association, 1975
- Discriminant Functions When Covariance Matrices are UnequalJournal of the American Statistical Association, 1974