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Raykov, Tenko; Marcoulides, George A.; Akaeze, Hope O. – Educational and Psychological Measurement, 2017
This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…
Descriptors: Comparative Analysis, Models, Statistical Analysis, Hierarchical Linear Modeling
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Grice, James W.; Yepez, Maria; Wilson, Nicole L.; Shoda, Yuichi – Educational and Psychological Measurement, 2017
An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…
Descriptors: Hypothesis Testing, Models, Observation, Statistical Inference
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Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando – Educational and Psychological Measurement, 2017
We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…
Descriptors: Research Methodology, Hypothesis Testing, Psychology, Social Science Research
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Jamil, Tahira; Marsman, Maarten; Ly, Alexander; Morey, Richard D.; Wagenmakers, Eric-Jan – Educational and Psychological Measurement, 2017
In 1881, Donald MacAlister posed a problem in the "Educational Times" that remains relevant today. The problem centers on the statistical evidence for the effectiveness of a treatment based on a comparison between two proportions. A brief historical sketch is followed by a discussion of two default Bayesian solutions, one based on a…
Descriptors: Bayesian Statistics, Evidence, Comparative Analysis, Problem Solving
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Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon; Penfield, Randall D. – Educational and Psychological Measurement, 2013
The Rasch model, a member of a larger group of models within item response theory, is widely used in empirical studies. Detection of uniform differential item functioning (DIF) within the Rasch model typically employs null hypothesis testing with a concomitant consideration of effect size (e.g., signed area [SA]). Parametric equivalence between…
Descriptors: Test Bias, Effect Size, Item Response Theory, Comparative Analysis
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Braver, Sanford L. – Educational and Psychological Measurement, 1975
The controversy regarding the admissibility of one-tailed tests of hypotheses was examined. Rather than taking a stand with regard to whether the one-or the two-tailed test is the most seriously flawed, a procedure is developed which can capitalize on the advantages of each. (RC)
Descriptors: Comparative Analysis, Hypothesis Testing, Prediction, Probability
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Nesselroade, John R.; Baltes, Paul B. – Educational and Psychological Measurement, 1970
Descriptors: Comparative Analysis, Factor Analysis, Factor Structure, Hypothesis Testing
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Levy, Kenneth J. – Educational and Psychological Measurement, 1975
Proposes three different multiple range tests based upon the Newman-Keuls philosophy with respect to significance levels. The three tests utilize the Fmax statistic, Cochran's statistic and a normalizing log transformation of the sample variances respectively. (Author/RC)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Statistical Significance
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Cooper, Martin – Educational and Psychological Measurement, 1975
A new test for increasing or decreasing trend in a set of observations is presented. Rather than making specific paired comparisons, as in the Cox and Stuart tests for trend, the user of the new test makes the comparisons of all possible pairs of observations. (Author)
Descriptors: Comparative Analysis, Hypothesis Testing, Nonparametric Statistics, Statistical Significance
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Shine, Lester C., II – Educational and Psychological Measurement, 1977
A series of independent, normally distributed events may be broken into intervals on an a priori basis. Then, within interval variance may be compared to among interval variance. These might be considered short-term and long-term variances. This concept and a test for comparing variances are presented. (Author/JKS)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Intervals
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Lienart, G. A. – Educational and Psychological Measurement, 1972
The G Index is the difference between the frequencies of the homonymly assigned cells and heteronymly assigned cells in a four-fold contingency table. (Author/MB)
Descriptors: Comparative Analysis, Hypothesis Testing, Mathematical Applications, Statistical Analysis
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Tarling, 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
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Keselman, H. J.; Toothaker, Larry E. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Research Methodology
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Barter, Alice – Educational and Psychological Measurement, 1974
Descriptors: College Students, Comparative Analysis, Hypothesis Testing, Performance
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Gaito, John – Educational and Psychological Measurement, 1978
The conduct of multiple post hoc comparison procedures following an analysis of variance is discussed. Various procedures are contrasted in terms of appropriateness, power, and other features. Octhogonal and nonorthogonal comparisons are discussed. (JKS)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Research Design
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