Stimulus programming in psychophysics

Summary and Conclusion The major thesis of this paper has been that one should choose a psychophysical method appropriate to the question which prompted the inquiry. It has been suggested that the method of constant stimuli, although not inappropriate for most questions, is by no means optimal for any particular question. A class of stimulus programming techniques called Markov designs has been briefly described. These have the principal advantage of using data as it is gathered to improve the selection of stimuli for the remainder of the experiment. This improvement is achieved by concentrating observations in the region of most interest. They are also reasonably easy to carry out and can be tailored to a wide range of experimental objectives, and pose no new problems in data analysis.Finally data analysis is discussed. It is pointed out that the question of which mathematical form to use in graduating the data is a minor one if the data are efficiently gathered and that, within reason, mathematical convenience is a good criterion. An advantage of the logistic function over the normal ogive is mentioned.Few of the ideas advanced here are new but many have not been appreciated fully by psychophysicists. The emphasis in this paper has been on the areas of sensitivity testing in which psychophysics has lagged behind best statistical practice, although it was pointed out that no efficient methods of analysis of the continuous response procedures have yet been devised by the statisticians. Better communication in both directions is clearly desirable.Operated with support from the United States Army, Navy, and Air Force.