Degree Of Agreement Quantitative Or Qualitative
The following contingency table applies to the more general problem of comparing two evaluators using an rating scale to any number of categories – not necessarily two, as in our discussion up to this point. The row and column amounts are ai. = ai1 +…+ aik or a.i = a1i +…+ aki. The total frequency of compliance p0 is expressed as p0 = 1/n × (a11 + a22 + . + akk), i.e. p0 equal to the sum of the diagonal entries in the contingency table divided by the sample size. Now, two independent stochastic evaluators would correspond to a frequency pe that we calculate as pe = a1./n × a.1/n + a2./n × a.2/n +…+ a?. /n × a.k/n ##,, i.e. pe is the sum of the products of the limit frequencies that relate to each diagonal input of the general contingency table. Cohens kappa for categories k is defined in the same way as before for k = 2, namely by the formula ?k = (p0-pe) /(1-pe). Background: Methods for the systematic control of qualitative studies are emerging.
Within the evidence review community, there is skepticism about the extent to which these review results will be reproducible (and some would argue whether they should be reproducible). To date, few “qualitative” evaluations have been published and it is difficult to assess the integrity of this nascent methodology. The inter-examiner agreement (in quantitative works called inter-rater reliability) concerns the coherence (or other) of the interpretation and, therefore, the authenticity (valid in quantitative works) of the synthesis. The extraction and synthesis of the qualitative results of the research is carried out through a process of interpretation. Interpretative authenticity is best demonstrated when several evaluators of different cultures and attitudes generate synthetic results from the same studies with a clear similarity in meaning. A more meaningful representation of these links is the so-called Bland Altman diagram, illustrated for both examples in Figures 2a and 2b. As before, each pair of measures is represented at the x-y level, but in a different way: the average of the two measures is represented as an x coordinate and the difference between them as a y coordination. In addition, the average value of all differences is represented as a horizontal line and two additional horizontal lines (pointed) are represented above and below this line at a distance of 1.96 times the standard deviation of the differences. These two lines correspond to what are called the limits of concordance. The average value of all differences indicates a systematic deviation between the two measurement techniques, for which a correction can usually be introduced; compliance limits indicate the size of other deviations that generally cannot be corrected. If the measured quantity is normally redistributed, 5% of the measured differences shall exceed the conformity limits, i.e.
more than 1,96 standard deviation above or below the mean of all differences (2). For simplicity, factor 2 is often used instead of 1.96; This last point, however, corresponds more precisely to the figure of 97.5% of the normal distribution. .