Some multiple correlation and predictor selection methods

The Doolittle, Wherry-Doolittle, and Summerfield-Lubin methods of multiple correlation are compared theoretically as well as by an application in which a set of predictors is selected. Wherry's method and the Summerfield-Lubin method are shown to be equivalent; the relationship of these methods to the Doolittle method is indicated. The Summerfield-Lubin method, because of its compactness and ease of computation, and because of the meaningfulness of the interim computational values, is recommended as a convenient least squares method of multiple correlation and predictor selection.     

Stimulus correlates of visual pattern discrimination by monkeys: Multidimensional analyses

Fourteen monkeys were presented with a series of simultaneous discrimination problems, each problem consisting of two visual metric patterns, and Ss’ performance was analyzed with respect to several physical dimensions of the patterns. Proficiency of discriminative performance was found to be directly and almost exclusively related to the extent to which the two patterns, when translated, had unique parts.