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Todd Horowitz; The high prevalence effect meets the low prevalence effect. Journal of Vision 2018;18(10):519. doi: 10.1167/18.10.519.
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A large body of research has examined the low prevalence effect (LPE) in visual search. Observers are more likely to miss targets at low prevalence (e.g., 1%-2%), compared to medium prevalence (50%). However, the effects of high prevalence (> 50%) have been comparatively neglected. In a recent meta-analysis (Horowitz, T. S. 2017. Prevalence in visual search: From the clinic to the lab and back again. Japanese Psychological Research, 59(2), 65–108), I demonstrated that the available data on the LPE are consistent with a criterion shift account: in signal detection terms, low prevalence induces a conservative bias, but does not change sensitivity. Here I compile the published data on high prevalence and compare the high prevalence effect (HPE) to the LPE. The summary effect sizes for sensitivity (d') were both negligible (LPE: g = 0.04, 95% CI -0.21 to +0.29; HPE: g = 0.55, 95% CI -0.40 to +1.51). However, the effect sizes for criterion (c) were significantly negative for both the LPE (g = -2.44, 95% CI -3.11 to -1.77) and the HPE (g = -6.57, 95% CI -8.76 to -4.38), indicating that criterion was more conservative at lower prevalence and more liberal at higher prevalence. These findings support the idea that both the LPE and the HPE can be explained within a unified theoretical framework. I also present meta-regression analyses detailing how different stimulus types and observer populations modulate the results.
Meeting abstract presented at VSS 2018
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