This study used eye-tracking to explore attention allocation to human and dog faces in children and adolescents with autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), and typical development (TD). Significant differences were found among the three groups. TD participants looked longer at the eyes than ASD and ADHD ones, irrespective of the faces presented. In spite of this difference, groups were similar in that they looked more to the eyes than to the mouth areas of interest. The ADHD group gazed longer at the mouth region than the other groups. Furthermore, groups were also similar in that they looked more to the dog than to the human faces. The eye tracking technology proved to be useful for behavioral investigation in different neurodevelopmental disorders.

We assessed several agreement coefficients applied in 2x2 contingency tables, which are commonly applied in research due to dichotomization. Here, we not only studied some specific estimators but also developed a general method for the study of any estimator candidate to be an agreement measurement. This method was developed in open-source R codes and it is available to the researchers. We tested this method by verifying the performance of several traditional estimators over all possible configurations with sizes ranging from 1 to 68 (total of 1,028,789 tables). Cohen’s kappa showed handicapped behavior similar to Pearson’s r, Yule’s Q, and Yule’s Y. Scott’s pi, and Shankar and Bangdiwala’s B seem to better assess situations of disagreement than agreement between raters. Krippendorff’s alpha emulates, without any advantage, Scott’s pi in cases with nominal variables and two raters. Dice’s F1 and McNemar’s chi-squared incompletely assess the information of the contingency table, showing the poorest performance among all. We concluded that Cohen’s kappa is a measurement of association and McNemar’s chi-squared assess neither association nor agreement; the only two authentic agreement estimators are Holley and Guilford’s G and Gwet’s AC1. The latter two estimators also showed the best performance over the range of table sizes and should be considered as the first choices for agreement measurement in contingency 2x2 tables. All procedures and data were implemented in R and are available to download from Harvard Dataverse https://doi.org/10.7910/DVN/HMYTCK.