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Peer reviewedKruskal, J. B. – Psychometrika, 1971
Descriptors: Mathematical Models, Mathematics, Multiple Regression Analysis, Statistical Analysis
Peer reviewedCapra, J. R.; Elster, R. S. – Educational and Psychological Measurement, 1971
This method of generating multivariate data differs from previous techniques in that it uses Crout factorization to develop the desired variance-covariance matrix. (Author/CK)
Descriptors: Computer Programs, Mathematical Models, Mathematics, Multiple Regression Analysis
Lord, Frederic M. – 1972
The stepped-up reliability coefficient does not have the same standard error as an ordinary correlation coefficient. Fisher's Z -transformation should not be applied to it. Appropriate procedures are suggested. (Author)
Descriptors: Analysis of Variance, Mathematical Models, Research, Research Reports
Peer reviewedVillegas, C. – Journal of Multivariate Analysis, 1976
A multiple time series is defined as the sum of an autoregressive process on a line and independent Gaussian white noise or a hyperplane that goes through the origin and intersects the line at a single point. This process is a multiple autoregressive time series in which the regression matrices satisfy suitable conditions. For a related article…
Descriptors: Mathematical Models, Matrices, Maximum Likelihood Statistics, Orthogonal Rotation
Peer reviewedTucker, Ledyard R. – Psychometrika, 1972
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Mathematics
Peer reviewedde Leeuw, Jan – Psychometrika, 1988
Multivariate distributions are studied in which all bivariate regressions can be linearized by separate transformation of each of the variables. A two-stage procedure, first scaling the variables optimally and then fitting a simultaneous equations model, is studied in detail. (SLD)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Mathematical Models
Peer reviewedHakstian, Ralph A.; Skakun, Ernest N. – Multivariate Behavioral Research, 1976
Populations of factorially simple and complex data were generated with first the oblique and orthogonal factor models, and then solutions based on special cases of the general orthomax criterion were compared on the basis of these characteristics. The results are discussed and implications noted. (DEP)
Descriptors: Comparative Analysis, Factor Analysis, Mathematical Models, Matrices
Peer reviewedRennie, Robert R.; Villegas, C. – Journal of Multivariate Analysis, 1976
An asymptotic theory is developed for a new time series model introduced in TM 502 289. An algorithm for computing estimates of the parameters of this time series model is given, and it is shown that these estimators are asymptotically efficient in that they have the same asymptotic distribution as the maximum likelihood estimators. (Author/RC)
Descriptors: Algorithms, Analysis of Covariance, Mathematical Models, Matrices
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
Moore, William E. – 1970
The previous theoretical development of the Poisson process as a strong model for the true-score theory of mental tests is discussed, and additional theoretical properties of the model from the standpoint of individual examinees are developed. The paper introduces the Erlang process as a family of test theory models and shows in the context of…
Descriptors: Arithmetic, Goodness of Fit, Grade 10, Mathematical Models
PDF pending restorationRosmann, Michael R. – 1973
When repeated measures are obtained on the same subjects, interobservation dependencies frequently are generated. The major ways in which these dependencies can arise are illustrated and it is shown how these dependencies may invalidate the use of analysis of variance (ANOVA) and its extension, trend analysis, as methods of evaluating the data of…
Descriptors: Analysis of Variance, Correlation, Goodness of Fit, Hypothesis Testing


