  A new Thurstonian rating scale model uses a variable decision rule (VDR) that
incorporates three previously formulated, distinct decision rules. The model
includes probabilities for choosing each rule, along with Gaussian
representation and criterion densities. Numerical optimisation techniques were
validated through demonstrating that the model fits simulated data tightly. For
simulations with 400 trials per stimulus (tps), useful information emerged
about the generating parameters. However, larger experiments (e.g. 4000 tps)
proved desirable for better recovery of generating parameters and to support
trustworthy choices between competing models by the Akaike Information
Criterion. In reanalyses of experiments by others, the VDR model explained most
of the data better than did classical signal detection theory models.
