MAXIMUM LIKELIHOOD ESTIMATION IN THE GENERALIZED CASE OF THURSTONE'S MODEL OF COMPARATIVE JUDGMENT

Abstract

In light of the empirical evidence against simple scalability a generalized case of Thurstone's model of comparative judgment was proposed, in which covariance terms in discriminal processes are not necessarily assumed zero or constant. In order to avoid the indeterminacy (over-parametrization) problem of the model, the covariance matrix was assumed to have a prescribed rank. A parameter estimation procedure based on the maximum likelihood principle was developed and implemented in the form of a FORTRAN program. An example was given to illustrate the empirical relevance of the proposal.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 34 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.