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The Interval Consensus Model: Aggregating Continuous Bounded Interval Responses.

Matthias Kloft1, Björn S Siepe1, Daniel W Heck1

  • 1Department of Psychology, https://ror.org/01rdrb571Philipps-Universität Marburg, Germany.

Psychometrika
|November 4, 2025
PubMed
Summary
This summary is machine-generated.

We introduce a new Interval Consensus Model (ICM) to find shared knowledge for unknown truths, extending Cultural Consensus Theory (CCT) to estimate consensus intervals from continuous bounded interval responses.

Keywords:
Bayesian modelingcontinuous bounded responsescultural consensus theoryinterval responses

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Area of Science:

  • Social Sciences
  • Statistics
  • Cognitive Science

Background:

  • Cultural Consensus Theory (CCT) aggregates shared knowledge for unknown truths.
  • Existing CCT models focus on point truths (dichotomous, polytomous, continuous).
  • Domains like risk assessment require consensus on intervals, not just points.

Purpose of the Study:

  • Introduce the Interval Consensus Model (ICM) as an extension of CCT.
  • Enable estimation of consensus intervals from continuous bounded interval responses.
  • Address limitations of existing CCT models for interval-based consensus.

Main Methods:

  • Developed a novel Bayesian hierarchical modeling approach.
  • Estimated latent consensus intervals from interval responses.
  • Utilized a simulation study to evaluate model performance.

Main Results:

  • The ICM effectively estimates consensus intervals.
  • ICM outperformed simple means and medians in simulation studies.
  • Applied the ICM to empirical data on verbal quantifier judgments.

Conclusions:

  • The ICM is a valuable extension of CCT for interval-based consensus.
  • This model enhances understanding in domains requiring interval judgments.
  • The ICM offers a statistically robust method for aggregating interval data.