Multidimensional scaling is a technique for determining spatial patterns of stimuli and is available in, for example, SPSS and SAS. The input takes the form of a matrix of either similarities or dissimilarities. These can either be calculated by the statistical package from raw data, and expressed in the form of distances, or evaluated directly from a subject by the tester. For example a subject might have their reaction times (RTs) taken for identifying semantic meaning of words from groups of semantic categories such as animals, people and household objects. A pair of stimuli(a,b) would have a value equal to the average RT for stimulus b when it is immediately preceded by stimulus a. The higher the value of the dissimilarity between a pair of stimuli the further that pair of stimuli are apart e.g. distance, RT. Conversely the higher a similarity between a pair of stimuli the closer together they are e.g. correlation.

[:FAQ:mds:level Choice of level of measurement]