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McSweeney, Maryellen; Schmidt, William H. – Journal of Educational Statistics, 1977
The relationship between quantitative predictor variables and the probability of occurrence of one or more levels of a qualitative criterion variable can be analyzed by quantal response techniques. This paper presents and discusses two quantal response models, comparing them to multiple linear regression and discriminant analysis. (Author/JKS)
Descriptors: Discriminant Analysis, Mathematical Models, Multiple Regression Analysis, Predictor Variables
Harris, Richard J. – 1992
Interpretation of emergent variables on the basis of structure coefficients (zero order correlations between original and emergent variables) is potentially very misleading and should be avoided in favor of interpretation on the basis of scoring coefficients. This is most apparent in multiple regression analysis and its special case, two-group…
Descriptors: Correlation, Discriminant Analysis, Mathematical Models, Multiple Regression Analysis
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Murphy, Kevin R. – Multivariate Behavioral Research, 1982
When either regression models or subjectively-weighted models are used as aids in making placement decisions, the discriminant validity of these models is questioned. The validity of several regression models and of subjectively weighted models was investigated in two experiments. (Author/JKS)
Descriptors: College Admission, Discriminant Analysis, Higher Education, Mathematical Models
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Bruno, James Edward; Nelkin, Ira – Educational Planning, 1975
The logit methodology provides a unique way of examining input-output relationships for social systems where the principal output of the analysis is a probability of some action or state. (Author)
Descriptors: Discriminant Analysis, Educational Planning, Educational Policy, Elementary Secondary Education
Schumacker, Randall E. – 1989
The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…
Descriptors: Comparative Analysis, Discriminant Analysis, Equations (Mathematics), Factor Analysis
Newman, Isadore – 1988
The nature and appropriate application of the technique of multivariate analysis are discussed. More specifically, the intent of the paper is to demystify and explain the use of multivariate analysis as well as provide guidelines for selection of the most effective statistics for use in specific situations. For the purpose of this paper, the term…
Descriptors: Analysis of Covariance, Analysis of Variance, Chi Square, Discriminant Analysis
Huberty, Carl J. – 1971
This study was concerned with various schemes for reducing the number of variables in a multivariate analysis. Two sets of illustrative data were used; the numbers of criterion groups were 3 and 5. The proportion of correct classifications was employed as an index of discriminatory power of each subset of variables selected. Of the four procedures…
Descriptors: Cluster Analysis, Correlation, Criteria, Discriminant Analysis