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.     

Computer use in psychology instruction

This paper presents the ways in which psychology departments are using microcomputers for instruction, the types of facilities that they are using, and the varieties of hardware that they employ. These data are related to other data reported over the past 10 years. In addition, a summary of the types of software currently available in all areas of psychology is presented, and areas in which there is a need for further software development are identified. The information reviewed in this paper was compiled from the current software listings available through COMPSYCH, as well as the results of a survey distributed to registered users of COMPSYCH who hold academic positions.     

Towards a theory of algorithm-determined cognitive test construction

A rationale for, and data from, a trial of a theory of item generation by algorithms whose origins are cognitive models of task performance are presented. Since Spearman (1904), intelligence has been operationally defined and assessed in human subjects by administering identical test items whose content and order have been fixed only after empirical iterations. In our approach, intelligence is ostensively defined by theoretically determined algorithms used for item construction and presentation. Knowledge of what cognitive factors limit human performance makes it possible to vary within tightly specified parameters those features of the tasks that contribute to difficulty, which we call radicals, to let those components of the tasks that do not contribute to difficulty vary randomly, and to counterbalance aspects of answer production that might induce biases of response. Empirical data are based on the generation of five different short tests demanding only functional literacy as a prerequisite for their execution. Four parallel forms of each test were administered to young male Army recruits whose scores were collated with their Army Entrance Test results, which were not previously known to us. Results show that the parallel, algorithm-generated item sets are statistically invariant, which item generation theory demands; and that the individual tests differentially predict Army Entrance Test scores. We conclude that IQ test performances are parsimoniously explained by individual differences in encoding, comparison and reconstructive memory processes.