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Peer reviewedLandrum, William L. – American Educational Research Journal, 1971
See EJ 030 376 and also TM 500 285 in this issue. (CK)
Descriptors: Analysis of Variance, Analytical Criticism, Mathematical Models, Statistical Analysis
Peer reviewedGebhardt, Friedrich – Psychometrika, 1971
Descriptors: Computer Programs, Factor Analysis, Goodness of Fit, Mathematical Models
Peer reviewedBray, James H.; Maxwell, Scott E. – Review of Educational Research, 1982
The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)
Descriptors: Analysis of Variance, Discriminant Analysis, Mathematical Models, Multivariate Analysis
Peer reviewedFischer, Gerhard H. – Psychometrika, 1981
Necessary and sufficient conditions for the existence and uniqueness of a solution of the so-called "unconditional" and the "conditional" maximum-likelihood estimation equations in the dichotomous Rasch model are given. It is shown how to apply the results in practical uses of the Rasch model. (Author/JKS)
Descriptors: Latent Trait Theory, Mathematical Models, Maximum Likelihood Statistics, Psychometrics
Peer reviewedVijn, Pieter; Molenaar, Ivo W. – Journal of Educational Statistics, 1981
In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)
Descriptors: Aptitude Treatment Interaction, Bayesian Statistics, Mastery Tests, Mathematical Models
Peer reviewedPlewis, Ian – Journal of Educational Statistics, 1981
Simple Markov models are fitted to a small sample of longitudinal categorical data of teachers' ratings of children's classroom behavior. Although the data consist only of observations at five occasions, it was possible, after dividing the data into two groups, to fit plausible models in continuous time. (Author/BW)
Descriptors: Longitudinal Studies, Mathematical Models, Research Problems, Statistical Analysis
Peer reviewedSachar, Jane – Journal of Experimental Education, 1980
The partial correlation coefficient is derived analytically under exemplary factor patterns. In these patterns, variables are described as an additive composition of a set of orthogonal factors, including general, common, and specific factors. Viewed in this framework, it is evident that the partial correlation may yield spurious results.…
Descriptors: Correlation, Factor Analysis, Factor Structure, Mathematical Models
Peer reviewedMacready, George B.; Dayton, C. Mitchell – Journal of Educational Statistics, 1980
Data evolving from processes which are developmental or hierarchical in nature are often analyzed by using latent class or latent structure models. A procedure for estimating such models when the model is not "identifiable" is presented. (JKS)
Descriptors: Data Analysis, Developmental Psychology, Developmental Tasks, Mathematical Models
Peer reviewedPeng, Chao-Ying, J.; Subkoviak, Michael J. – Journal of Educational Measurement, 1980
Huynh (1976) suggested a method of approximating the reliability coefficient of a mastery test. The present study examines the accuracy of Huynh's approximation and also describes a computationally simpler approximation which appears to be generally more accurate than the former. (Author/RL)
Descriptors: Error of Measurement, Mastery Tests, Mathematical Models, Statistical Analysis
Peer reviewedMassy, William F. – Management Science, 1976
A difference equation model of a university budget system is proposed and analyzed. The conditions for first-order and second-order dynamic equilibrium are determined, and it is shown that first-order equilibrium provides a useful criterion for financial health. (Author/JG)
Descriptors: Budgeting, College Administration, Educational Finance, Higher Education
Peer reviewedBaker, Frank B. – Review of Educational Research, 1977
Recent advances in item analysis have provided greater capabilities for the analysis of tests, but have also significantly increased the gap between the theory and practice of item analysis. This paper traces the lines of development in item analysis under latent trait theory. (MV)
Descriptors: Correlation, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewedJohnes, Geraint – Journal of Education Finance, 1996
Develops a theoretical model to evaluate universities' preference for teaching or research, using data from 25 British research universities for 1985-86 and 1991-92. Universities' utility functions have changed slightly; the relative weight attached to research has risen, whereas that attached to teaching has fallen. Institutional specialization…
Descriptors: College Faculty, Higher Education, Instruction, Mathematical Models
Peer reviewedBusk, 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
Peer reviewedMuthen, Bengt O. – Psychometrika, 1989
The problems posed for latent variable analysis by populations with different sets of parameter values are discussed. An overview of methodology to address heterogeneity is presented, including a review of structural modeling by the multiple indicator-multiple causes model and the use of the LISCOMP computer program. (SLD)
Descriptors: Data Analysis, Equations (Mathematics), Estimation (Mathematics), Mathematical Models
Peer reviewedSanders, P. F.; And Others – Psychometrika, 1989
A new method is presented for determining the minimum number of observations per subject needed to achieve a specific generalizability coefficient. The method, consisting of a branch-and-bound algorithm, enables an investigator to specify an acceptable threshold for generalizability coefficients. (SLD)
Descriptors: Equations (Mathematics), Generalizability Theory, Mathematical Models, Observation


