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Use of egocentric networks and recall error challenges exist but can be managed.
Here an interaction in the construction of prototypes is optimized so that the bidirectional recall error can be minimized.
Such mappings are constructed in a way so that the recall processes (both one-directional and bidirectional) lead to the recalled items characterized by a minimal recall error.
In Experiment 2, a short-term recall task was administered using 16 lists of three CVC pseudo-Pinyin syllables and recall error patterns were analyzed.
Furthermore we discuss an optimization of the distance function used in the clustering algorithm realized with regard to the recall error.
The recall error is discussed with regard to the essential parameters of the FCM (the number of clusters and the fuzzification coefficient).
A second limitation concerns recall error.
Estimates from HY, eliminating recall error, were highly compatible.
We emphasise the distinction between recall error and recall bias.
Alternative calculations based on headache yesterday (with little recall error) produced, for all headache, a corroborating 1.7%.
An important limitation of our study, as previously mentioned, is that retrospective self-report may be prone to recall error.
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