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Small, Melinda Y.; Butterworth, John – Child Development, 1981
Tests semantic integration and frequency tally models of memory among 60 first-, third-, and fifth-grade children. Data from third and fifth graders show different patterns of results for regular and anomalous stories. The true-inference error rate was significantly greater than the error rates for false premise and false-inference sentences in…
Descriptors: Abstract Reasoning, Elementary Education, Elementary School Students, Hypothesis Testing
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Thomas, Hoben – Journal of Experimental Child Psychology, 1980
A procedure for evaluating the Genevan stage learning hypothesis is illustrated by analyzing Inhelder, Sinclair, and Bovet's guided learning experiments (in "Learning and the Development of Cognition." Cambridge: Harvard University Press, 1974). (Author/MP)
Descriptors: Children, Cognitive Development, Developmental Stages, Evaluation
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Humphreys, Lloyd G. – Journal of Educational Psychology, 1980
Many researchers, including Buriel (EJ 187 987), incorrectly compared the results in each study with null hypotheses of zero differences between means or zero population correlations. Instead, a test of difference between the mean differences in the two samples or the direct comparison of the two sample correlations is required. (Author/CP)
Descriptors: Comparative Analysis, Correlation, Hypothesis Testing, Mathematical Formulas
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Dyer, Frank J. – Educational and Psychological Measurement, 1980
Power analysis is in essence a technique for estimating the probability of obtaining a specific minimum observed effect size. Power analysis techniques are applied to research planning problems in test reliability studies. A table for use in research planning and hypothesis testing is presented. (Author)
Descriptors: Hypothesis Testing, Mathematical Formulas, Power (Statistics), Probability
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Williams, John D. – Journal of Experimental Education, 1979
Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Statistical Analysis
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Kazdin, Alan E. – Journal of Educational Statistics, 1980
Problems associated with randomization tests in single- case experiments are discussed. This article follows a discussion of randomization tests in single case studies in the same issue of this journal. (See TM 505 799; 505 801).(Author/JKS)
Descriptors: Experimental Groups, Hypothesis Testing, Research Design, Research Problems
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Hollingsworth, Holly H. – Educational and Psychological Measurement, 1980
If heterogeneous regression slopes are present in analysis of covariance (ANCOVA), the likelihood of committing a Type I error is greater than what had been prespecified. The power of the ANCOVA test of hypothesis for all possible differences of treatment effects is not maximized. (Author/RL)
Descriptors: Analysis of Covariance, Hypothesis Testing, Mathematical Models, Power (Statistics)
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Williams, Bruce W. – Journal of Personality and Social Psychology, 1980
Four levels of the behavior constraint-reinforcement variable were manipulated: attractive reward, unattractive reward, request to perform, and a no-reward control. Only the unattractive reward and request groups showed the performance decrements that suggest the overjustification effect. It is concluded that reinforcement does not cause the…
Descriptors: Behavior Modification, Children, Hypothesis Testing, Motivation
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Levy, Kenneth J. – Journal of Experimental Education, 1978
The purpose of this paper is to demonstrate how many more subjects are required to achieve equal power when testing certain hypotheses concerning proportions if the randomized response technique is employed for estimating a population proportion instead of the conventional technique. (Author)
Descriptors: Experimental Groups, Hypothesis Testing, Research Design, Response Style (Tests)
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Shine, Lester C., II – Educational and Psychological Measurement, 1979
The Shine-Bower error term is used to form approximate F ratios for testing various effects in the Shine-Bower single-subject ANOVA and the Shine Combined ANOVA. Results demonstrate the utility of these F ratios with respect to the probability of a type I error. (Author/JKS)
Descriptors: Analysis of Variance, Case Studies, Hypothesis Testing, Nonparametric Statistics
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Milligan, Glenn W. – Educational and Psychological Measurement, 1979
A FORTRAN program is provided for calculating the power of statistical tests based on the chi-square distribution. The program produces approximations to the exact probabilities obtained from the noncentral chi-square distribution. The calculation of the noncentrality parameter is discussed for tests of independence and goodness of fit.…
Descriptors: Computer Programs, Goodness of Fit, Hypothesis Testing, Nonparametric Statistics
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Newman, Isadore; Thomas, Jay – Multiple Linear Regression Viewpoints, 1979
Fifteen examples using different formulas for calculating degrees of freedom for power analysis of multiple regression designs worked out by Cohen are presented, along with a more general formula for calculating such degrees of freedom. (Author/JKS)
Descriptors: Hypothesis Testing, Mathematical Models, Multiple Regression Analysis, Power (Statistics)
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Swaminathan, Hariharan; DeFriesse, Frederick – Educational and Psychological Measurement, 1979
A problem in analysis of variance is that after rejection of the overall hypothesis, no contrasts of interest are found to be significant. A procedure for determining the contrast of significance is outlined, and the relationship between the "most significant" contrast and the overall test is shown. (Author/JKS)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Statistical Significance
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James, Michael – Educational and Psychological Measurement, 1979
Details are given for the use of the mixed effects multivariate analysis of variance table provided by the BMD12V computer program to compute raw generalized variances and hence the U and F statistics for the mixed effects model. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Hypothesis Testing, Program Descriptions
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Boik, Robert J. – Educational and Psychological Measurement, 1979
A simple rationale for Scheffe's Method and Gabriel's Simultaneous Test Procedure is presented. Examples of both methods are provided. (Author)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Statistical Significance
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