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<p>Are people who are susceptible to one illusion also susceptible to others? Previous research has shown small correlations, but might small values reflect attenuation from measurement error from trial-to-trial variation? To assess measurement error, we develop a set of novel data visualizations and hierarchical models. Data from 149 participants on two variants of the five illusions were collected using an adjustment paradigm. The results showed low trial-noise and strong between-subject variability (e.g., signal-to-noise ratio <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\approx 1.14\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>≈</mo> <mn>1.14</mn> </mrow> </math></EquationSource> </InlineEquation>, reliability <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\approx 0.93\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>≈</mo> <mn>0.93</mn> </mrow> </math></EquationSource> </InlineEquation>). Correlations across illusions are low, around <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(0.22 \pm 0.07\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>0.22</mn> <mo>±</mo> <mn>0.07</mn> </mrow> </math></EquationSource> </InlineEquation>. A Bayesian hierarchical analysis reveals minimal attenuation from measurement error in these values. Though correlations are low, latent variable analysis reveals a common latent factor that loads on all tasks and explains about 23.3% of the variance in illusion susceptibility.</p>

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Localizing structure in individual differences: A visual illusion case study

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • Mahbod Mehrvarz,
  • Hrithik Popat,
  • Jeffrey N. Rouder

摘要

Are people who are susceptible to one illusion also susceptible to others? Previous research has shown small correlations, but might small values reflect attenuation from measurement error from trial-to-trial variation? To assess measurement error, we develop a set of novel data visualizations and hierarchical models. Data from 149 participants on two variants of the five illusions were collected using an adjustment paradigm. The results showed low trial-noise and strong between-subject variability (e.g., signal-to-noise ratio \(\approx 1.14\) ≈ 1.14 , reliability \(\approx 0.93\) ≈ 0.93 ). Correlations across illusions are low, around \(0.22 \pm 0.07\) 0.22 ± 0.07 . A Bayesian hierarchical analysis reveals minimal attenuation from measurement error in these values. Though correlations are low, latent variable analysis reveals a common latent factor that loads on all tasks and explains about 23.3% of the variance in illusion susceptibility.