# Interrater Agreement Ratings

As noted above, pearson correlations are the most commonly used statistics when reliability between rats is assessed in the field of expressive vocabulary (e.g. B Bishop and Baird, 2001; Janus, 2001; Norbury et al., 2004; Bishop et al., 2006; Massa et al., 2008; Gudmundsson and Gretarsson, 2009) and this trend extends to other areas such as. B language deficiencies (e.g. B Boynton Hauerwas and Addison Stone, 2000) or learning difficulties (z.B Van Noord and Prevatt, 2002). As noted above, linear correlations do not provide information on the rating agreement. They do, however, provide useful information about the relationship between two variables, here the vocabulary of two caregivers for the same child. In the specific case of the use of correlation coefficients as an indirect measure of rating resistance, linear associations can be expected, so that pearson correlations are an appropriate statistical approach. It cannot and should not be the only measure of reliability between boards, but it can be used as an assessment of the strength of the (linear) association. Correlation coefficients have the added benefit of allowing comparisons, for example. B in the study of group differences in relation to the strength of ratings.

Like most other studies evaluating the reliability of expression scores (only) report correlation coefficients, this measure also allows us to link the results of the pre-reguic study with the results of previous research. Therefore, we note correlations for each of the two scoring subgroups (parents-parents-teacher-pairs), we also compare them and also calculate the correlation of evaluations between the two subgroups. Another way to conduct reliability tests is the use of the intraclass correlation coefficient (CCI).  There are several types, and one is defined as „the percentage of variance of an observation because of the variability between subjects in actual values.“  The ICC area can be between 0.0 and 1.0 (an early definition of CCI could be between 1 and 1). CCI will be high if there are few differences between the partitions that are given to each item by the advisors, z.B. if all advisors give values identical or similar to each of the elements.