0.85 – 1.96 x 0.037 to 0.85 – 1.96 x 0.037, which is calculated on an interval between 0.77748 and 0.92252, a confidence interval of 0.78 to 0.92. It should be noted that the SE depends in part on the sample size. The higher the number of measured observations, the lower the expected standard error. While kappa can be calculated for relatively small sample sizes (z.B 5), IC should be broad enough for such studies, which will lead to a lack of « concordance » within the IC. As a general heuristic, the sample size should not be less than 30 comparisons. Sample sizes of 1000 or more are mathematically the most likely to produce very small CIS, which means that the estimate of match should be very accurate. A final concern about the reliability of advisors was introduced by Jacob Cohen, a leading statistician who, in the 1960s, developed key statistics to measure the reliability of interrater, Cohens Kappa (5). Cohen indicated that there will likely be some degree of match among data collectors if they do not know the correct answer, but if they simply guess. He assumed that a number of conjectures would be speculated and that insurance statistics should be responsible for this fortuitous agreement. He developed Kappa`s statistics as an understanding of this random agree factor.

Hernaez R, Lazo M, Bonekamp S, Kamel I, Brancati FL, Guallar E, Clark JM: Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology. 2011, 54: 1082-1090. Once the kappa is calculated, the researcher will probably want to assess the importance of the kappa received by calculating the confidence intervals for the received kappa. Percentage agreement statistics are a direct measure, not an estimate. There is therefore only a small need for confidence intervals. The Kappa is, however, an estimate of Interrater`s reliability and the confidence intervals are therefore more interesting. Pearson`s « R-Displaystyle, » Kendall format or Spearman`s « Displaystyle » can measure the pair correlation between advisors using an orderly scale.

Pearson believes that the scale of evaluation is continuous; Kendall and Spearman`s statistics only assume it`s ordinal. If more than two clicks are observed, an average match level for the group can be calculated as the average value of the R-Displaystyle r values, or « Displaystyle » of any pair of debtors. There are several operational definitions of « inter-rated reliability » that reflect different views on what a reliable agreement between advisors is. [1] There are three operational definitions of the agreement: Gwets AC1 offers a reasonable, probability-adjusted coefficient of agreement, corresponding to the percentage of the agreement. Gwet [13] explained that one of the problems with Cohens Kappa is that it gives a very wide range for e (K) – from 0 to 1 depending on the limit, while the e (K) values should not exceed 0.5. Gwet attributed this error to the poor methods used to calculate the probability of Kappa`s random agreement [9]. Theoretically, confidence intervals are represented by the kappa subtraction of the desired DE level value times the standard kappa error. As the most frequently desired value is 95%, Formula 1.96 uses as a constant to multiply the standard error of Kappa (SE). The formula for a confidence interval is as follows: this study was conducted in 67 patients (56% of men) aged 18 to 67 years, with an average SD of 44.13 ± 12.68 years.

Nine counsellors (7 psychiatrists, a psychiatrist and a social worker) participated as interviewers, either for the first or for the second, which took place 4 to 6 weeks apart. Interviews were conducted to establish a diagnosis of personality disorder (PD) based on DSM-IV criteria.