Definition
SSA – similarity structure analysis (previously called smallest space analysis) – is a geometric technique for aiding comprehension of the spatial structure of correlation matrices or similarity coefficients matrices among variables. In this technique, the data are treated intrinsically in terms of inequalities, needing no explicit prespecified model.
Description
Similarity structure analysis (SSA) was introduced and developed by Louis Guttman (1968) with the aim of overcoming the limitations of factor analysis regarding the possibility of the testing of hypotheses (Guttman 1954, 1958). Mathematically from the point of view of spatial analysis, Guttman regarded factor analysis to be “but a special case of Smallest Space Analysis” (Guttman 1967, p. 78; 1982, p. 491). Details regarding the differences between SSA and factor analysis are to be found inter alia in Guttman (1967, 1982), Schlesinger and Guttman (1969), and Cohen (2003).
SSAis essentially a geometric technique....
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References
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This entry is dedicated to the memory of Professor Adi Raveh, who passed away in July 2012, before the completion of this enterprise.
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Amar, R., Levy, S. (2023). SSA: Similarity Structure Analysis. In: Maggino, F. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Cham. https://doi.org/10.1007/978-3-031-17299-1_2840
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