The missing values can only be taken into account by Fleiss` K if all observations with missing values are excluded. In contrast, for Krippendorffs Alpha, all observations with at least two evaluations are included in the calculation. We examined the robustness of the two coefficients at missing values in MCAR conditions with respect to average distortion and type 1 empirical type 1 error for three scenarios (I. No. 100, No. 5, K – 2, Low Concordance; II. No. 100, No. 5, K-5, High Compliance; III. No. 100, No.
10, K – 3, Medium Agreement; See also the Methods section). Krippendorff`s Alpha was very resistant to the lack of values, even though 50% of the values were missing. In contrast, Fleiss` K was impartial at only 10% of the missing values in all three scenarios. For 50% of the missing data, the distortion in all three scenarios was greater than 20% and the probability of coverage was less than 50% (Table 1). Mitchell, S. K. (1979). Interobserver agreement, reliability and generalization of data collected in observational studies. Psychol. Bull.
86, 376-390. doi: 10.1037/0033-2909.86.2.376 To sum up, this report has two main objectives: a methodological tutorial for assessing reliability, Consistency and linear correlation of evaluation pairs and assess whether the German parental questionnaire ELAN (Bockmann and Kiese-Himmel, 2006) can also be reliably used with Kita teachers for the evaluation of early vocabulary development. We compared mother-father and parent-teacher evaluations in terms of agreement, correlation and reliability of evaluations. We also looked at the factors related to children and advice that influence the adequacy and reliability of advice. In a relatively homogeneous group of predominantly middle-class families and high-quality kite environments, we expected high matching and a linear correlation of assessments. This report uses a set of concrete data to demonstrate how a complete assessment of reliability between credit rating agencies, the agreement between the rating agencies (concordataire) and the linear correlation between credit ratings can be achieved and notified. On the basis of this example, we want to divert often confusing evaluation aspects and thus contribute to improving the comparability of future rating analyses. Through a tutorial, we want to promote the transfer of knowledge. B in pedagogical and therapeutic contexts where methodological requirements for the comparison of ratings are too often ignored, leading to misinterpretation of empirical data.