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Peer reviewedMuthen, Bengt; Christoffersson, Anders – Psychometrika, 1981
A new method is proposed for a simultaneous factor analysis of dichotomous responses from several groups of individuals. The method makes it possible to compare factor loading pattern, factor variances and covariances, and factor means over groups. Generalized least squares is used as the estimation procedure. (Author/JKS)
Descriptors: Data Analysis, Factor Analysis, Goodness of Fit, Hypothesis Testing
Peer reviewedTversky, Amos; Gati, Itamar – Psychological Review, 1982
The coincidence hypothesis predicts that dissimilarity between objects that differ on two separable dimensions is larger than predicted from their unidimensional differences on the basis of triangle inequality and segmental additivity. The coincidence hypothesis was supported in two-dimensional stimuli studies. (Author/CM)
Descriptors: Classification, Discriminant Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedRonis, David L. – Educational and Psychological Measurement, 1981
Many researchers draw the conclusion that one independent variable has more impact than another without testing the null hypothesis that their impact is equal. This paper presents and recommends a technique for testing the relative magnitude of effects, rather than basing conclusions solely on descriptive statistics. (Author/BW)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Research Design
Peer reviewedBagozzi, Richard P. – Multivariate Behavioral Research, 1981
Canonical correlation analysis is considered to be a general model for bivariate and multivariate statistical methods. Some problems involving assumptions and statistical tests for parameters exist for social science data. A resolution for these problems is presented by treating canonical correlation as a special case of linear structural…
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedRamsey, Philip H. – Journal of Educational Statistics, 1980
Disagreements have arisen about the robustness of the t test in normal populations with unequal variances. Employing liberal but objective standards for assessing robustness, it is shown that the t test is not always robust to the assumption of equal population variances even when sample sizes are equal. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedHill, P. W.; McGaw, B. – American Educational Research Journal, 1981
In an attempt to resolve conflicting conclusions arising from an investigation of the validity of the claimed psychological properties of Bloom's taxonomy, the LISREL method was applied to the data of Kropp and Stoker. The simplex assumption was supported when the knowledge category is deleted from the taxonomy. (Author/RL)
Descriptors: Classification, Factor Structure, Goodness of Fit, Hypothesis Testing
Peer reviewedRothstein, Stuart M.; And Others – Psychometrika, 1981
A nonparametric test of dispersion with paired replicates data is described which involves jackknifing logarithmic transformations of the ratio of variance estimates for the pre- and posttreatment populations. Results from a simulation show that the test performs well under the null hypothesis and has good power properties. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Nonparametric Statistics
Peer reviewedSmall, 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
Peer reviewedThomas, 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
Peer reviewedHumphreys, 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
Peer reviewedDyer, 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
Peer reviewedWilliams, 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
Peer reviewedKazdin, 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
Peer reviewedHollingsworth, 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)
Peer reviewedWilliams, 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


