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Games, Paul A. – American Educational Research Journal, 1975
A brief introduction is presented on how multiple regression and linear model techniques can handle data analysis situations that most educators and psychologists think of as appropriate for analysis of variance. (Author/BJG)
Descriptors: Analysis of Variance, Mathematical Models, Multiple Regression Analysis, Reliability
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Wherry, Robert J., Sr. – Personnel Psychology, 1975
The major portion of this article considered the multiple regression model, used for industrial prediction situations, and fourteen separate episodes the author discussed in trying to make that model work. (Author/RK)
Descriptors: Attitudes, Industrial Personnel, Mathematical Models, Multiple Regression Analysis
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Winkler, Dwight D.; McNamara, James F. – Planning and Changing, 1975
Outlines the facts being presented in the literature about mathematical models, their related components, and their practical and theoretical uses. (Author)
Descriptors: Educational Administration, Mathematical Applications, Mathematical Models, Models
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Wittmann, E. – International Journal of Mathematical Education in Science and Technology, 1975
In this paper the mathematical structures of Bourbaki, the Piagetian developmental structures, and Polya's heuristic structures are compared. (SD)
Descriptors: Comparative Analysis, Learning, Mathematical Models, Mathematics
Arrowsmith, Gary – PASAA: Notes and News about Language Teaching and Linguistics in Thailand, 1974
A universal separation of speech and language is described by the use of one mathematical frame of reference. Also described are the accruing new comparisons and measurements made possible by a theoretically adequate separation of speech and language. (Author/RM)
Descriptors: Articulation (Speech), Language, Linguistic Theory, Linguistics
Smawley, Robert R. – J Exp Educ, 1969
Descriptors: Analysis of Variance, Mathematical Models, Research Design, Research Methodology
Rodger, R. S. – 1974
A fairly large number of different methods exist for evaluating comparisons or null hypothetical contrasts. Because it is difficult to choose among them, this paper develops a 2 by 2 classification of the methods. The first dimension of the classification is decision-based error rate vs. experimentwise error rate. The second dimension is planned…
Descriptors: Classification, Evaluation Methods, Hypothesis Testing, Mathematical Models
Cook, Linda L.; Eignor, Daniel R. – 1981
The purposes of this paper are five-fold to discuss: (1) when item response theory (IRT) equating methods should provide better results than traditional methods; (2) which IRT model, the three-parameter logistic or the one-parameter logistic (Rasch), is the most reasonable to use; (3) what unique contributions IRT methods can offer the equating…
Descriptors: Equated Scores, Latent Trait Theory, Mathematical Models, Test Construction
Hedges, Larry V. – 1981
When the results of a series of independent studies are combined, it is useful to quantitatively estimate the magnitude of the effects. Several methods for estimating effect size are compared in this paper. Glass' estimator and the uniformly minimum variance unbiased estimator are based on the ratio of the sample mean difference and the pooled…
Descriptors: Literature Reviews, Mathematical Models, Maximum Likelihood Statistics, Sample Size
Lehrer, Richard – 1981
Log linear models are proposed for the analysis of structural relations among multidimensional developmental contingency tables. Model of quasi-independence are suggested for testing specific hypothesized patterns of development. Transitions in developmental categorizations are described by Markov models applied to successive contingency tables. A…
Descriptors: Developmental Stages, Goodness of Fit, Mathematical Models, Statistical Analysis
Rigdon, Steven E.; Tsutakawa, Robert K. – 1981
Estimation of ability and item parameters in latent trait models is discussed. When both ability and item parameters are considered fixed but unknown, the method of maximum likelihood for the logistic or probit models is well known. Discussed are techniques for estimating ability and item parameters when the ability parameters or item parameters…
Descriptors: Algorithms, Latent Trait Theory, Mathematical Formulas, Mathematical Models
Lord, Robert E.; And Others – 1981
The purpose of this study was to evaluate the parallel processing impact of multiple-instruction multiple-data path (MIMD) computers on flight simulation software. Basic mathematical functions and arithmetic expressions from typical flight simulation software were selected and run on an MIMD computer to evaluate the improvement in execution time…
Descriptors: Computer Programs, Computers, Flight Training, Mathematical Formulas
Bryk, Anthony; Woods, Elinor – 1980
This resource book examines the value-added model approach when used in assessing early childhood Title I (ECT-I) programs. The evaluation design must be able to separate program effects from natural maturation. The basic idea behind the value-added model builds on the notion of natural maturation. The major strengths are that it does not require…
Descriptors: Early Childhood Education, Evaluation Methods, Federal Programs, Mathematical Models
Kalsbeek, William D.; And Others – 1975
The National Assessment of Educational Progress; Second Science Assessment No-Show Study assessed the magnitude and causation of nonresponse biases. A No-Show is defined as an individual who was selected as a sample respondent but failed to be present for regular assessment of the 17-year-old group. The procedure whereby a sample of eligible…
Descriptors: Educational Assessment, High Schools, Mathematical Models, Performance Factors
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Phelps, James L.; Addonizio, Michael F. – 1979
This paper, one of three related documents, examines statewide trends in the distribution of staff in the Michigan public schools. Along with its related documents, it provides a basis for analyzing the impact of state financing mechanisms and funding levels on the overall distribution of resources throughout the state and on the resource…
Descriptors: Educational Finance, Equal Education, Mathematical Models, School Districts
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