In the 21st century we are nearing the time when treatment of ocular disease is becoming a reality. As such, the ability to monitor disease progression and/or disease recovery is as important as the ability to detect disease related ocular change. Minimising measurement variability is intrinsic to monitoring accurately any chosen ocular-visual biomarker that best represents disease progression over time. This is the topic of the paper by Gilmore and co-workers in this issue of BJO (p 1462). These authors have described the measurement variability of the short wavelength (SW) automated perimetry (SWAP) in patients with diabetes. SWAP has been used primarily to detect vision loss and to monitor progressive visual field loss in glaucoma.¹ SWAP is more sensitive in detecting glaucomatous changes than standard white on white (WW) perimetry.² Gilmore and co-workers used the psychophysical frequency of seeing analysis as a measure of within examination variability, where the slope of the frequency of seeing curve represents threshold variability. Earlier Chauhan and co-workers³ integrated a psychophysical frequency of seeing paradigm into WW automated perimetry testing. They found that in patients with glaucoma and those with suspicion of glaucoma the variability in frequency of seeing was not necessarily explained by the response threshold or threshold deviation. Change in the slope of the frequency of seeing curve probably represents …