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Peer reviewedKeselman, H. J.; And Others – Educational and Psychological Measurement, 1981
This paper demonstrates that multiple comparison tests using a pooled error term are dependent on the circularity assumption and shows how to compute tests which are insensitive (robust) to this assumption. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Models, Research Design, Statistical Significance
Peer reviewedHollingsworth, Holly H. – Educational and Psychological Measurement, 1981
If the null hypothesis of a one-sample test of multivariate means is rejected, the dimension of the line joining the population centroid and the hypothesized centroid can be interpreted with a linear function, using a discriminant function and the correlation of each dependent variable with a discriminant score. (Author/BW)
Descriptors: Discriminant Analysis, Hypothesis Testing, Mathematical Models, Statistical Analysis
Peer reviewedHazleton, Vincent; Riley, Patricia – Communication Quarterly, 1981
Communication researchers have recently expressed concern with the lack of statistical power in their literature. Authors propose a method for increasing statistical power: the partitioning of the decision region in three parts. This procedure results in an unambiguous interpretation of nonsignificant results and leads to increased power. (PD)
Descriptors: Communication Research, Research Methodology, Research Problems, Statistical Analysis
Peer reviewedHorn, John L.; Engstrom, Robert – Multivariate Behavioral Research, 1979
Cattell's scree test and Bartlett's chi-square test for the number of factors to be retained from a factor analysis are shown to be based on the same rationale, with the former reflecting subject sampling variability, and the latter reflecting variable sampling variability. (Author/JKS)
Descriptors: Comparative Analysis, Factor Analysis, Hypothesis Testing, Statistical Analysis
Peer reviewedKatz, Barry M.; McSweeney, Maryellen – Educational and Psychological Measurement, 1980
Errors of misclassification associated with two concept acquisition criteria and their effects on the actual significance level and power of a statistical test for sequential development of these concepts are presented. Explicit illustrations of actual significance levels and power values are provided for different misclassification models.…
Descriptors: Concept Formation, Hypothesis Testing, Mathematical Models, Power (Statistics)
Peer reviewedFeldt, Leonard S. – Psychometrika, 1980
Procedures are developed for testing the hypothesis that Cronbach's alpha reliability coefficient is equal for two tests given to the same subjects. (Author/JKS)
Descriptors: Error of Measurement, Hypothesis Testing, Measurement, Statistical Significance
Peer reviewedCohen, S. Alan; Hyman, Joan S. – Educational Researcher, 1979
The authors contend that most research in education lacks statistical power. They feel that the poor use of statistics as a tool for enhancing internal validity must be remediated. The adoption of a new convention is proposed in order to put statistical certainty into reasonable perspective. (RLV)
Descriptors: Educational Research, Hypothesis Testing, Predictive Validity, Statistical Analysis
Peer reviewedCeurvorst, Robert W. – Educational and Psychological Measurement, 1979
The Johnson-Neyman technique is briefly reviewed, and a program for carrying out an analysis using the procedure is described. The program accommodates one independent and one dependent variable, up to 20 groups of observations, and an unlimited number of cases. (Author)
Descriptors: Analysis of Covariance, Computer Programs, Correlation, Program Descriptions
Sullivan, Jeremy R. – Research in the Schools, 2001
Summarizes the post-1994 literature in psychology and education regarding statistical significance testing, emphasizing limitations and defenses of statistical testing and alternatives or supplements to statistical significance testing. (SLD)
Descriptors: Educational Research, Literature Reviews, Psychological Studies, Research Methodology
Peer reviewedKosciulek, John F.; Szymanski, Edna Mora – Rehabilitation Counseling Bulletin, 1993
Provided initial assessment of the statistical power of rehabilitation counseling research published in selected rehabilitation journals. From 5 relevant journals, found 32 articles that contained statistical tests that could be power analyzed. Findings indicated that rehabilitation counselor researchers had little chance of finding small…
Descriptors: Power (Statistics), Rehabilitation Counseling, Research Methodology, Scholarly Journals
Peer reviewedSpyridakis, Jan H.; And Others – Journal of Technical Writing and Communication, 1991
Addresses the need of technical communicators to become critical readers of empirical research. Presents simple definitions of selected research designs and statistical concepts. Accompanies these definitions with concrete examples related to the field of technical communication research. (SR)
Descriptors: Definitions, Higher Education, Research Design, Statistical Significance
Kaufman, Alan S. – Research in the Schools, 1998
Three articles in this special issue explore issues related to the use and misuse of statistical significance testing, the major methodological issue in current educational research. Comments on these articles and rejoinders by the authors of the first three articles explore additional aspects of statistical significance testing. (SLD)
Descriptors: Educational Research, Hypothesis Testing, Research Methodology, Statistical Significance
McLean, James E.; Ernest, James M. – Research in the Schools, 1998
Although statistical significance testing as the sole basis for result interpretation is a flawed practice, significance tests can be useful as one of three criteria that must be demonstrated to establish a position empirically. Statistical significance testing provides evidence that an event did not happen by chance but gives no evidence of the…
Descriptors: Educational Research, Hypothesis Testing, Research Methodology, Statistical Significance
Knapp, Thomas R. – Research in the Schools, 1998
Expresses a "middle-of-the-road" position on statistical significance testing, suggesting that it has its place but that confidence intervals are generally more useful. Identifies 10 errors of omission or commission in the papers reviewed that weaken the positions taken in their discussions. (SLD)
Descriptors: Educational Research, Hypothesis Testing, Research Methodology, Statistical Significance
Peer reviewedKellow, J. Thomas – American Journal of Evaluation, 1998
Many evaluation students are still being taught the use of tests of statistical significance without being warned about their limitations. This paper discusses other estimates of treatment effects necessary to interpret between-group differences correctly. Sources to improve evaluation practice are also suggested. (SLD)
Descriptors: Estimation (Mathematics), Evaluation Utilization, Groups, Probability


