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Hung, Su-Pin; Chen, Po-Hsi; Chen, Hsueh-Chih – Creativity Research Journal, 2012
Product assessment is widely applied in creative studies, typically as an important dependent measure. Within this context, this study had 2 purposes. First, the focus of this research was on methods for investigating possible rater effects, an issue that has not received a great deal of attention in past creativity studies. Second, the…
Descriptors: Item Response Theory, Creativity, Interrater Reliability, Undergraduate Students
Anderson, Carolyn J.; Hsieh, Ju-Shan – 1996
When the highest-way association is present in a 3-way cross-classification of frequencies, standard logit and loglinear models have an many parameters as there are cells in the table; that is, the models are "saturated." Extensions of logit and loglinear models are described here that provide more parsimonious alternatives to saturated…
Descriptors: Interaction, Mathematical Models, Predictor Variables, Scaling
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Busk, Patricia L.; Marascuilo, Leonard A. – Australian Journal of Education, 1989
An extension of the discussion of loglinear models presents post hoc procedures for statistically evaluating treatment effects, contrasts, and confidence intervals, illustrating methods for main effect and interaction contrasts and paying special attention to odds ratios and their interval estimates. Procedures for treating variables as…
Descriptors: Estimation (Mathematics), Hypothesis Testing, Interaction, Mathematical Models
Betz, M. Austin – 1976
Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…
Descriptors: Analysis of Variance, Hypothesis Testing, Interaction, Mathematical Models
Bart, William M.; Palvia, Rajkumari – 1983
In previous research, no relationship was found between test factor structure and test hierarchical structure. This study found some correspondence between test factor structure and test inter-item dependency structure, as measured by a log-linear model. There was an inconsistency, however, which warrants further study: more significant two-item…
Descriptors: Factor Structure, Interaction, Latent Trait Theory, Mathematical Models
Pohlmann, John T. – 1972
The Monte Carlo method was used, and the factors considered were (1) level of main effects in the population; (2) level of interaction effects in the population; (3) alpha level used in determining whether to pool; and (4) number of degrees of freedom. The results indicated that when the ratio degrees of freedom (axb)/degrees of freedom (within)…
Descriptors: Analysis of Variance, Computer Programs, Factor Analysis, Hypothesis Testing
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Thompson, Bruce – 1989
The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…
Descriptors: Analysis of Covariance, Analysis of Variance, Heuristics, Hypothesis Testing
Pennell, Roger – 1970
A model and a computer program for performing conjoint measurement is developed. (AG)
Descriptors: Algorithms, Analysis of Variance, Computer Programs, Goodness of Fit
Levin, Joel R.; Marascuilo, Leonard A. – 1971
Marascuilo and Levin's (1970) notion of Type IV errors is extended, with respect to the interpretation of interactions in analysis of variance (ANOVA) designs. To help clarity what an interaction is and what it is not, in terms of the ANOVA model, the following points are made: (i) interactions should be thought of as linear contrasts involving…
Descriptors: Analysis of Variance, Behavioral Science Research, Evaluation Methods, Hypothesis Testing
Hall, Charles E. – 1971
A set of symbols is presented along with logical operators which represent the possible manipulations of the linear model. The use of these symbols and operators is to simplify the representation of analysis of variance models, correlation models and factor analysis models. (Author)
Descriptors: Analysis of Variance, Computer Programs, Correlation, Factor Analysis
Angoff, William H. – 1972
A technique for detecting and studying item (or test) x group interactions independent of differences in level or dispersion of the groups is described. It involves construction of a scatter plot with two groups represented, one on each axis. Each point in the scatter plot represents the coordinates of a measure of a characteristic for one group…
Descriptors: Analysis of Covariance, Cluster Analysis, Comparative Analysis, Correlation
Thomas, David B. – 1971
Two educational computer simulations are described in this paper. One of the simulations is STATSIM, a series of exercises applicable to statistical instruction. The content of the other simulation is comprised of mathematical learning models. Student involvement, the interactive nature of the simulations, and terminal display of materials are…
Descriptors: Behavioral Science Research, Computer Oriented Programs, Display Systems, Educational Environment
Borich, Gary D. – 1972
Statistical procedures are presented for determining ordinal and disordinal aptitude-treatment interactions with linear and curvilinear data. The paper presents a method for testing the homogeneity of group regressions for a single aptitude and provides models for expanding this test to linear and curvilinear regression planes. Procedures are…
Descriptors: Aptitude Tests, Correlation, Factor Analysis, Interaction