Predicted values of ΔITD determined from acuity data.

A, Relationship between localization acuity (Δθ), just-noticeable difference in ITD identification (ΔITD) and the angular variation of ITD. B, Example of how ΔITDs are determined for each individual data point in an acuity data set. C, Candidate models for ΔITD distributions across ITD. Uniform distributions are described by parameter c₀ and linear distributions are described by parameters c_p and k_p. D, Best-fit uniform or linear distributions for each acuity data set under consideration. Overall goodness of fit is similar for both distributions. Midline predictions of ΔITD are better for the linear distribution, but the proportionality constant is low in all cases and negative in one case (Schmidt data), making them close to the uniform case.