August 2019
Volume 19, Issue 9
Open Access
Erratum  |   August 2019
Corrections
Journal of Vision August 2019, Vol.19, 14. doi:https://doi.org/10.1167/19.9.14
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      Corrections. Journal of Vision 2019;19(9):14. https://doi.org/10.1167/19.9.14.

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      © ARVO (1962-2015); The Authors (2016-present)

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CORRECTIONS TO: Oberauer, K., Stoneking, C., Wabersich, D., & Lin, H.-Y. (2017). Hierarchical Bayesian measurement models for continuous reproduction of visual features from working memory. Journal of Vision, 17(5):11, 1–27, https://doi.org/10.1167/17.5.11
There was an error in the R script for analyzing the data of Experiment 1 in this article: For each trial, an array of eight colors assigned to eight locations had been produced; only the first n had been presented depending on set size n, but all eight were included in the data set. The analysis script sorted these colors and their locations by their spatial distance to the target, without removing the not-presented colors/locations first. As a consequence, in trials with n between 2 and 7, some not-presented colors/locations were erroneously included in the analysis whereas some presented ones were excluded. We are grateful for Nicholas Lange (University of Warwick) for alerting us to this error. The error is now corrected in the scripts posted on the Open Science Framework: osf.io/wjg7y/
Below are corrected versions of the table and the two figures that were affected by this error. The correction changed the WAIC values and the parameter estimates only by very small amounts and has no implications for the conclusions drawn in the article. The table and two figures have been corrected in the article online. 
Original Table 1
Original Table 1
Corrected Table 1
 
WAIC values of the mixture model and the interference measurement model for Experiment 1.
Corrected Table 1
 
WAIC values of the mixture model and the interference measurement model for Experiment 1.
Original Figure 20
Original Figure 20
Corrected Figure 20
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical mixture model as a function of set size (Experiment 1).
Corrected Figure 20
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical mixture model as a function of set size (Experiment 1).
Original Figure 21
Original Figure 21
Corrected Figure 21
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical IMM as a function of set size (Experiment 1).
Corrected Figure 21
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical IMM as a function of set size (Experiment 1).
Original Figure 20
Original Figure 20
Corrected Figure 20
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical mixture model as a function of set size (Experiment 1).
Corrected Figure 20
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical mixture model as a function of set size (Experiment 1).
Original Figure 21
Original Figure 21
Corrected Figure 21
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical IMM as a function of set size (Experiment 1).
Corrected Figure 21
 
Estimated parameters (means and 95% HDIs of posteriors) of the hierarchical IMM as a function of set size (Experiment 1).
Original Table 1
Original Table 1
Corrected Table 1
 
WAIC values of the mixture model and the interference measurement model for Experiment 1.
Corrected Table 1
 
WAIC values of the mixture model and the interference measurement model for Experiment 1.
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