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Purpose: For consideration as a safety and efficacy endpoint in clinical trials, contrast sensitivity (CS) must be measured at multiple spatial frequencies. We developed two non-parametric hierarchical Bayesian models (HBM) to enable advanced statistical inference on CS estimated with qCSF.

Methods: The HBMc and HBMv computed the joint posterior CS distribution at six traditional spatial frequencies (1, 1.5, 3, 6, 12, and 18 cpd) across the population, individual and test levels. The HBMc incorporated covariance hyperparameters at the population and individual levels to capture the relationship between CSs across SFs; HBMv did not. In addition, we applied a Bayesian inference procedure (BIP) to estimate the posterior CS distribution from each qCSF test independently. The three procedures were applied to a dataset of 112 subjects tested with qCSF 50 trials in each of three (L, M, & H) luminance conditions …