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W F Bischof

Publications and source records attributed to W F Bischof.

21 records · Page 2Linked to original sources

Bootstrap variance estimators for the parameters of small-sample sensory-performance functions.

The bootstrap method, due to Bradley Efron, is a powerful, general method for estimating a variance or standard deviation by repeatedly resampling the given set of experimental data. The method is applied here to the problem of estimating the standard deviation of the estimated midpoint and spread of a sensory-performance function based on data sets comprising 15-25 trials. The performance of the bootstrap estimator was assessed in Monte Carlo studies against another general estimator obtained by the classical "combination-of-observations" or incremental method. The bootstrap method proved clearly superior to the incremental method, yielding much smaller percentage biases and much greater efficiencies. Its use in the analysis of sensory-performance data may be particularly appropriate when traditional asymptotic procedures, including the probit-transformation approach, become unreliable.

Animals↗

Beyond the displacement limit: an analysis of short-range processes in apparent motion.

If a circle of random dots is presented in two successive displays in which the second is rotated in relation to the first, then observers are able to accurately discriminate the direction of apparent rotation as long as the rotation is small. Rotations beyond this short-range apparent motion can produce the impression of motion in the reverse direction. The performance in identifying the direction of rotation further depends on the eccentricity of stimulation and the density of the random dots. Simulations of the experiments using the Marr and Ullman model of motion detection are in good quantitative agreement with the data except for low dot density patterns and large displacements. In these situations perception seems to be dominated by the operation of long-range processes.

Discrimination, Psychological↗

Selective internal operations in the recognition of locally and globally point-inverted patterns.

Performance in discriminating rotated 'same' patterns from 'different' patterns may decrease with rotation angle up to about 90 degrees and then increase with angle up to 180 degrees. This anomalously improved performance under 180 degrees pattern rotation or point-inversion can be explained by assuming that patterns are internally represented in terms of local features and their spatial-order relations ('left of', 'above', etc.), and that, in pattern comparison, an efficient internal sense-reversal operation occurs (transforming 'left of' to 'right of', etc.). Previous experiments suggested that local features and spatial relations could not be efficiently separated in some pattern-comparison tasks. This hypothesis was tested by measuring 'same-different' discrimination performance under four transformation: point-inversion 1 of the whole pattern, point-inversion 1F of local features alone, point-inversion 1P of local-feature positions alone, and identity transformation Id. The results suggested that internal sense-reversal operations could be applied selectively and efficiently, provided that local features were well separated. Under this condition performances for 1F and 1 were about the same whereas performance for 1P was significantly worse, the latter performance resulting possibly from an attempt to apply internal global and local sense-reversal operations serially.

Adult↗