Modeling Uncertainty around Free-list Cultural Salience Scores

Abstract

The free-list method has enjoyed a remarkably productive history, yet most free-list research is limited to informal comparisons that are heavily reliant on point estimates such as item or cultural salience. Here, we demonstrate a range of methods to incorporate uncertainty into such group-level estimates. This approach involves: (1) resampling individual-level data (via bootstrapping or Bayesian regression) to create a range of hypothetical alternative samples; (2) generating group-level estimates (e.g., Smith’s S) in each sample; and (3) using the variation in these estimates as uncertainty intervals. While we focus predominantly on cultural salience, this approach can be applied to other free-list metrics. We also present some extensions to this approach, such as comparing estimates between items and between groups. We provide open data and code to help readers gain familiarity with these methods. Ultimately, we encourage researchers using free-list data to move beyond simply reporting point estimates.