As soon as your company experiences a more agile analysis of the contract and the results are displayed in your KPI, you can feel safer when it comes to making new business commitments. Setting up new agreements will be much easier if you have your entire library on hand during the negotiation. You will then be able to work more efficiently and take bolder steps in the growth of your business. Gwets AC1 is the statistic of choice for two evaluators (Gwet, 2008). The Gwet concordance coefficient can be used in more contexts than kappa or pi, as it does not depend on the acceptance of independence between evaluators. Note that the Gwet concordance coefficient does not depend on the assumption of independence between evaluators, so you can use it to reflect the magnitude of the concordance in more contexts than kappa. But more importantly, if Evisort is used as part of a comprehensive contract analysis process, it helps you avoid natural human errors resulting from manual contract review. This helps reduce risk, as errors in contract management can lead to costly pitfalls. Contract analysis can add value to your company`s end result, as contracts form the basis of any business cooperation. Think of them as the software for business. We all know that “errors” in software cause machines to run inefficiently. In the same way, contracts can contain errors affecting the profits of their business. Among these errors include: – the number of subjects evaluated, w the weight for concordance or disagreement, po the share of observed concordance, pe the expected share of concordance, pij the fraction of evaluations i by the first evaluator and j by the second evaluator, and therefore the default error for the examination is that the kappa statistic is equal to zero.
Maxwell test statistics, which are statistically very significant, show that evaluators have significant discrepancies in at least one category. McNemar`s widespread statistics show that discrepancies are not evenly distributed. Disagreement on each category and asymmetry of disagreements (2 evaluators) Compliance analysis with more than two evaluators is a complex and controversial subject, see Fleiss (1981, p. 225). Weighted Kappa compensates in part for a non-weight kappa problem, namely that it is not adapted to the degree of disagreement. Disagreements are weighted by reducing the priority from top left (origin) of the table. StatsDirect uses the following definitions for weight (1 is the default parameter): statistically very significant z-tests show that we have the zero assumption that the evaluations are independent (i.e. .