For this agreement index, a value is calculated if you question a value for a combination (combine) or an overreoliment (D_Sequence). This figure is in turn about 100% if the object in question connects as well as expected and decreases in proportion to the probability if the combination is not very likely. The value can also increase by more than 100% if the deal is exceptionally good. The value of A`n is about 60% for a wide range of n-values. This is the justification for taking 60% as the threshold for the acceptance of individual convergence indices. The argument for the same threshold for Aoverall and Amodel is that we expect ln(F) to pass by chance from 0 if we increase the number of parameters. This threshold gets the symbol: it is then taken as the acceptance threshold for each agreement index. Another approach to the use of compliance indices is the use of outlier analysis. When outlier analysis is used, the compliance index continues to be calculated (see details below). The most useful definition of the global agreement is therefore as follows: we sometimes see documents and presentations that misinterpret compliance indices as values that indicate a very likely pattern (e.B.g.
riede and Edinborough Reference Riede and Edinborough2012). OxCal`s correspondence indices are similar to Bayes factors, a type of calculation used to compare the probability of Bayes models (Gilks et al. Reference Gilks, Richardson and Spiegelhalter1996; Kruschke Reference Kruschke2014). It is important that OxCal`s compliance indices are not actual bay factors, but pseudo bayes factors and should only be used to determine whether a model is consistent or inconsistent (Bronk Ramsey Reference Bronk Ramsey1995: 427-428, Reference Bronk Ramsey2001: 355). Indices are numerical values for the concordance between the OxCal model and the data. Values below 60 indicate that the chronological data and model are inconsistent, while values above 60 indicate consistency (Bronk Ramsey Reference Bronk Ramsey 1995: 427-428), the value of 60% of the 95% probability in a chi-square trial is similar. Amodel provides a value for the conformity of the entire model, and Aoverall is a function of the correspondence indices of each data. It is a simple framework between the two distributions. We will come back to the question of the threshold for accepting the agreement as good – which turns out to be around 60% for most purposes. We can also calculate the logarithmic mean of each match index needed to pass the same test by calculating the A`n, where: For simple combinations generated from the Combine(), D_Sequence or &-operator function, there is only one independent parameter. . .