Duffy, Huttenlocher, Hedges, and Crawford (2010, Psychonomic Bulletin & Review, 17[2], 224-230) examined whether the well-established central tendency bias in people's reproductions of stimuli reflects bias toward the mean of an entire presented distribution or bias toward only recently seen stimuli. They reported evidence that responses were biased toward the long-run mean and found no evidence that they were biased toward the most recent stimuli. Duffy and Smith (2018) reexamine the data using a different analytical strategy and argue that estimates are biased by recent stimuli rather than toward the long-run mean. I argue that this reanalysis misses a true effect of the running mean and that the data are (mostly) consistent with the claims in the original work. I suggest that these results, and many other null results presented by Duffy and Smith, do not have major theoretical significance for the category adjustment model and similar Bayesian models. (Code and data available: https://osf. io/tkqvn.)
Keywords Human memory . Statistical inference . CategorizationAt issue in earlier work by Duffy, Huttenlocher, Hedges, and Crawford (2010, hereafter called DHHC) was whether the well-established central tendency bias in people's reproductions of stimuli reflects bias toward the mean of an entire distribution or bias toward recently seen stimuli. DHHC reported evidence that responses were biased toward the long-run mean rather than toward the most recent stimuli and presented these results as consistent with the category adjustment model (CAM), a Bayesian model of stimulus estimation (Huttenlocher, Hedges, & Vevea, 2000). In their reexamination, Duffy and Smith (DS; 2018) point out some flaws in the original work, apply a different analytical approach to the data, and conclude that estimates are biased toward recent stimuli rather than toward the running mean. They interpret their findings as a refutation of CAM, and of Bayesian models more generally. Here, I argue that the DS failure to detect the impact of the running mean on estimates is likely a Type II error. I also suggest that the paper overstates the theoretical significance of its findings and of the original findings reported in DHHC, and that it presents a distorted view of CAM.