Multi-parameter utility and drift-rate functions conflate attribute weights and choice consistency

Standard decision models include two components: subjective-value (utility) functions and stochastic choice rules. The first establishes the relative weighting of the attributes or dimensions and the second determines how consistently the higher utility option is chosen. For a decision problem with M attributes, researchers often estimate M-1 utility parameters and separately estimate a choice-consistency parameter. Instead, researchers sometimes estimate M parameters in the utility function and neglect choice consistency. I argue that while these two approaches are mathematically identical, the latter conflates utility and consistency parameters, leading to ambiguous interpretations and conclusions. At the same time, behavior arises from the interaction of utility and consistency parameters, so for choice prediction they should not be considered in isolation. Overall, I advocate for a clear separation between utility functions and stochastic choice rules when modeling decision-making, and reinforce the notion that researchers should use M-1 parameters for M-attribute decision problems.