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Birnbaum, Robert – J Educ Res, 1970
Descriptors: Academic Achievement, Admission Criteria, Community Colleges, Hypothesis Testing
McEwen, William J.; Greenberg, Bradley S. – J Commun, 1969
Descriptors: Attitude Change, Communication (Thought Transfer), Hypothesis Testing, Information Theory
Peer reviewedBetz, M. Austin; Levin, Joel R. – Journal of Educational Statistics, 1982
Logically consistent hypothesis-testing for factorial analysis of variance designs is proposed in the context of a hierarchical model. It is shown that all of the hypotheses associated with the traditional factorial model are conceptually independent and occupy the lowest levels of the hierarchy. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Models
Peer reviewedCantor, Joan H.; Spiker, Charles C. – Journal of Experimental Child Psychology, 1982
Strategies of kindergarten children in discrimination learning were studied in a factorial design with temporal placements of two introtact probes and two types of pretraining. Results support the expectation that the posttrial probe would improve the short-term efficiency of children in both pretraining conditions. (Author/MP)
Descriptors: Cognitive Ability, Discrimination Learning, Hypothesis Testing, Kindergarten Children
Frentz, Thomas S. – Southern Speech Communication Journal, 1983
Argues that reliance upon verification procedures has inhibited theory building in communication. Advances four falsification procedures and presents examples from communication studies. Offers several implications these procedures have for empirical research in communication. (PD)
Descriptors: Behavioral Science Research, Communication Research, Hypothesis Testing, Research Methodology
Peer reviewedTarling, Roger – Educational and Psychological Measurement, 1982
The Mean Cost Rating, P(A) from Signal Detection Theory, Kendall's rank correlation coefficient tau, and Goodman and Kruskal's gamma measures of predictive power are compared and shown to be different transformations of the statistic S. Gamma is generally preferred for hypothesis testing. Measures of association for ordered contingency tables are…
Descriptors: Comparative Analysis, Hypothesis Testing, Power (Statistics), Predictive Measurement
Peer reviewedRogosa, David – Educational and Psychological Measurement, 1981
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance. (Author)
Descriptors: Hypothesis Testing, Mathematical Models, Predictor Variables, Regression (Statistics)
Peer reviewedVegelius, Jan – Educational and Psychological Measurement, 1981
The G index is a measure of the similarity between individuals over dichotomous items. Some tests for the G-index are described. For each case an example is included. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Nonparametric Statistics
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 reviewedBoik, Robert J. – Psychometrika, 1981
The validity conditions for univariate repeated measures designs are described. Attention is focused on the sphericity (equality of variance) requirement. It is recommended that separate rather than pooled error term procedures be routinely used to test a priori hypotheses. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Research Design
Peer reviewedHuynh, Huynh – Psychometrika, 1981
Procedures for the analysis of profiles of means in repeated measures designs under order restriction for patterns of mean change are described. Tables of critical values are provided for the case of simple-order alternatives. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Profiles
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 reviewedLee, Howard B.; Comrey, Andrew L. – Multivariate Behavioral Research, 1979
The popular factor analytic procedure of putting unities in the main diagonal and retaining all factors with an eigenvalue greater than one is criticized with respect to the number of factors retained and resultant estimates of common variance. Ways of avoiding these difficulties are discussed. (JKS)
Descriptors: Factor Analysis, Hypothesis Testing, Oblique Rotation, Orthogonal Rotation
Peer reviewedBlair, R. Clifford; Higgins, James J. – Journal of Educational Statistics, 1980
Monte Carlo techniques were used to compare the power of Wilcoxon's rank-sum test to the power of the two independent means t test for situations in which samples were drawn from (1) uniform, (2) Laplace, (3) half-normal, (4) exponential, (5) mixed-normal, and (6) mixed-uniform distributions. (Author/JKS)
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Formulas, Nonparametric Statistics


