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Lee, Sik-Yum; Song, Xin-Yuan; Lu, Bin – Multivariate Behavioral Research, 2007
This article proposes an intuitive approach for predictive discriminant analysis with mixed continuous, dichotomous, and ordered categorical variables that are defined via an underlying multivariate normal distribution with a threshold specification. The classification rule is based on the comparison of the observed data logarithm probability…
Descriptors: Factor Analysis, Discriminant Analysis, Probability, Monte Carlo Methods
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Chant, David; Dalgleish, Lenard I. – Multivariate Behavioral Research, 1992
A Statistical Analysis System (SAS) macro procedure for performing a jackknife analysis on structure coefficients in discriminant analysis is described together with issues and caveats about its use in multivariate methods. An example of use of the SAS macro is provided. (SLD)
Descriptors: Computer Software, Correlation, Discriminant Analysis, Error of Measurement
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Joachimsthaler, Erich A.; Stam, Antonie – Multivariate Behavioral Research, 1990
Mathematical programing formulas are introduced as new approaches to solve the classification problem in discriminant analysis. The research literature is reviewed, and an illustration using a real-world classification problem is provided. Issues relevant to potential uses of these formulations are discussed. (TJH)
Descriptors: Classification, Discriminant Analysis, Equations (Mathematics), Literature Reviews
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Cohen, Jacob; Lee, Robert S. – Multivariate Behavioral Research, 1987
STATGRAPHICS, a statistical package written for the IBM PC/XT/AT, is reviewed. In addition to superb graphics, STATGRAPHICS is unequalled in time series procedures, quality control, linear programming, and other mathematical procedures. The modules for regression analysis, categorical data analysis, and nonparametric analysis are good, but contain…
Descriptors: Analysis of Variance, Cluster Analysis, Computer Graphics, Computer Software