Methodological issues of using a class of neural networks called Mixture Density Networks (MDN) for discriminant analysis are discussed. MDN models have the advantage of having a rigorous probabilistic interpretation, and they have proven to be a viable alternative as a classification procedure in discrete domains. Both classification and…

THE STUDIES EMBODIED IN THIS REPORT PROPOSE SOME STATISTICAL METHODS OF ORDERING AND ATTAINING RELEVANCY TO HELP THE EDUCATIONAL RESEARCHER CHOOSE AMONG SUCH VARIABLES AS TESTS AND BEHAVIOR RATINGS. CONSTRUCTION OF A MODEL FOR THE ANALYSIS OF CONTINGENCY TABLES, DETERMINATION OF THE MOST APPROPRIATE ORDERING PRINCIPLE IN STEP-DOWN ANALYSIS FOR THE…

A WORKING MODEL CAPABLE OF RANKING INDIVIDUALS IN A RANDOM SAMPLE FROM A MULTIVARIATE POPULATION BY SOME CRITERION OF INTEREST WAS DEVELOPED. THE MULTIPLE CORRELATION COEFFICIENT OF RANKS WITH MEASURED VARIATES AS A STATISTIC IN TESTING WHETHER RANKS ARE ASSOCIATED WITH MEASUREMENTS WAS EMPLOYED AND DUBBED "QUASI-RANK MULTIPLE CORRELATION…