Individual Subitizing Range (ISR) calculator

Created by Tali Raveh at 2019-01-23 13:53:46, updated at 2019-01-24 09:55:22

Short description A matlab code that calculates subitizing range at the individual level based on response times from vocal enumeration task. The OSF link includes the code, a readMe file and a child-friendly OpenSesame vocal enumeration task.

Reference Leibovich-Raveh, T., Lewis, D. J., Al-Rubaiey Kadhim, S., & Ansari, D. (2018). A New Method for Calculating Individual Subitizing Ranges. Journal of Numerical Cognition, 2018, Vol. 4(2), 429–447, https://doi.org/10.5964/jnc.v4i2.74

Authors Tali Leibovich-Raveh, Daniel Jacob Lewis, Saja Al-Rubaiey Kadhim, Daniel Ansari


Comment by Attila Krajcsi (2019-03-16 15:18:01, updated at 2019-03-16 15:41:20)

Support

The work provides an individual subitizing range calculation method based on sigmoid fit: First it finds the parameters of the sigmoid fit, then based on these parameters, it finds the point where tangent line crosses the x-axis, which point can be seen as an “elbow point” close to the subitizing range (see Figure 3 of the paper, displayed below).

Figure 3

The method seems like a reasonable extension of the sigmoid fit method, and I can imagine that this could be useful, especially, when the data show a sigmoid-like pattern.

While the paper highlights some of the advantages of the sigmoid elbow point method, and stresses that it is superior to the bilinear fit method, the paper misses to discuss some relevant features of both methods that might modulate the conclusion.

Overall, the proposed method seems to be reasonable, even if I guess some arguments exaggerate the advantages of the sigmoid method over the bilinear method. Further works could sort out the specific distinctive properties of different methods and the conditions where one or the other method could be more beneficial.

Disclaimer: I was one of the reviewers for this paper.


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