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- W199470014 abstract "Various approaches combining the concepts of traditional representational theories of measurement with probabilistic notions are discussed. These approaches have been introduced as formal frameworks for measurement in the presence of error and variability. The material is presented from a systematic point of view. Emphasis is placed mainly on the following developments: (a) models in which the objects or events are represented by numbers with the underlying ‘empirical’ relations defined in probabilistic terms (e.g., Fechnerian scaling); (b) models in which the objects or events are represented by random variables (as e.g., random utility models). The article in particular covers recent developments concerning distribution-free random utility models. This approach may be considered a generalization of the concept of a binary choice system induced by rankings, which allows one to consider probabilistic mixtures not only of orderings but also other classes of deterministic measurement structures. Corresponding general representation and characterization theorems are outlined." @default.
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- W199470014 date "2001-01-01" @default.
- W199470014 modified "2023-09-27" @default.
- W199470014 title "Measurement Theory: Probabilistic" @default.
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- W199470014 doi "https://doi.org/10.1016/b0-08-043076-7/00597-0" @default.
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