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The I2 Statistic As Selection Bias Test: Updated Threshold Limits.

Steffen Mickenautsch1,2, Veerasamy Yengopal1

  • 1Faculty of Dentistry, University of the Western Cape, Cape Town, ZAF.

Cureus
|May 25, 2026
PubMed
Summary
This summary is machine-generated.

Revised I² thresholds enhance selection bias testing in randomized controlled trials (RCTs), increasing testable RCTs from 71% to 100%. This confirms a significant positive correlation between selection bias and effect estimates in RCTs.

Keywords:
bias testi2 testrandomized control trialsreview of clinical trialsselection biassystematic review and meta analysis

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Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Evidence-Based Medicine

Background:

  • Selection bias is a critical concern in randomized controlled trials (RCTs).
  • The simulated comparator trial (SCT)-based I² test is used to assess selection bias.
  • Existing I² point estimate threshold limits restrict the number of testable RCTs.

Purpose of the Study:

  • To revise the I² point estimate threshold limits for the SCT-based I² test to increase the proportion of testable RCTs.
  • To test the null hypothesis that trial effect estimates are not significantly positively correlated with selection bias levels.
  • To test the null hypothesis that effect estimates do not differ significantly between RCTs with low and high selection bias.

Main Methods:

  • Revised I² threshold limits were developed using RCT simulations.
  • 332 real-world RCTs were re-tested for selection bias using the revised limits.
  • Spearman's rank correlation and independent samples t-tests were used to test the null hypotheses.

Main Results:

  • The proportion of testable RCTs increased from 71% to 100% with the revised thresholds.
  • A statistically significant, small positive correlation was found between absolute risk difference (RD) values and selection bias levels (B%) (Spearman's rho = 0.268, p < 0.0001).
  • RCTs with high selection bias showed a significantly higher mean absolute RD (0.18) compared to those with low selection bias (0.10) (t = -4.65, p < 0.0001).

Conclusions:

  • Revised threshold limits significantly improved the utility of the I² test for selection bias assessment in RCTs.
  • Both null hypotheses were rejected, confirming a significant positive relationship between selection bias and effect estimates.
  • The established relationship between selection bias and effect estimates is robust and independent of the revised I² threshold limits.