1. Introduction -- Definition of data theory -- Objectives of this monograph -- 2. Measurement -- Measurement as theory testing -- Levels of measurement -- 3. Data theory -- Data as a geometric model -- Coomb's theory of data -- An alternative theory of data -- The importance of data theory -- 4. Dimensionality -- Dimensionality as variation among objects -- Dimensionality as a mathematical model -- Physical versus conceptual dimensions -- Scaling and dimensional analysis -- Scaling results and interpreting dimensions -- 5. Data theory and scaling methods -- Single stimulus data -- Stimulus comparison data -- Similarities data -- Perferential choice data -- Interpretations of data -- 6. Alternating least squares, optimal scaling -- 7. Conclusions
Analysis
Social sciences Statistical analysis
Research methods and evaluation in the social sciences
Notes
(Quantitative applications in the social sciences ; no. 78)
