Clues to aural discrimination

Five measures of the items of the Multiple-Choice Intelligibility Test were obtained: apparent aural similarity of the four words available to a listener on hearing a stimulus, interconsonantal differences among the prevocalic portions of these words, phonemic discrepancies among these words, distinctive feature differences among these words, and the pooled discrimination score of the four words that were available to the responder on hearing the stimulus. The last score was made the target in a multiple correlation problem, and the relative contribution, combined and separately, of the four remaining measures to the target measure was determined. These four measures accounted for approximately 45% of the variance among the scores of discrimination. The strongest contributors were apparent aural similarity of the available responses and the phonemic discrepancy among the available responses.     

Cognitive efficiency modes in old age: performance on sequential and coordinative verbal and visuospatial tasks

In an experiment using a large set of verbal and spatial tasks requiring low or high degrees of executive control, 3 distinct age-related effects were found. The smallest effect (no slowing) was tied to lexical tasks with low executive involvement, the largest deficit (age-related slowing factor of 2.2) was tied to visuospatial tasks with high executive involvement, an intermediate level of deficit (slowing factor of 1.7) was found for visuospatial tasks with low executive load and verbal tasks with high executive load. These age-related dissociations were incompatible with any "common cause" formulation. The mechanism responsible for the dissociation between verbal and visual tasks, and between low and high executive load remains to be determined. The latter may reflect capacity limits.     

Using segmented linear regression models with unknown change points to analyze strategy shifts in cognitive tasks

Some years ago, Beem (1993, 1995) described a program for fitting two regression lines with an unknown change point (Segcurve). He suggested that such models are useful for the analysis of a variety of phenomena and gave an example of an application to the study of strategy shifts in a mental rotation task. This technique has also proven to be very fruitful for investigating strategy use and strategy shifts in other cognitive tasks. Recently, Beem (1999) developed SegcurvN, which fitsn regression lines with (n - 1) unknown change points. In the present article we present this new technique and demonstrate the usefulness of a three-phase segmented linear regression model for the identification of strategies and strategy shifts in cognitive tasks by applying it to data from a numerosity judgment experiment. The advantages and shortcomings of this technique are evaluated.