This seems to be the same as a perzentile method first described by Bland and Altman [5], except that, in the case of repeated measures, we use the start resampling to get the upper limit. Although it does not adopt a normal distribution, we must nevertheless consider that the differences are independent and distributed identically. Other non-parametric methods are available [31, 32]. Stevens [33] also developed a generalization of the probability of concordance based on the moment method, which does not require any distribution assumptions for true values. Some of which are known and often used in the literature, and others that include recent advances in compliance research. Based on a predefined share of p = 0.95 to limit differences between devices, the IDI was calculated from 95% to 10.9 (CI 9.4 to 12.7) based on a square mean deviation of 30.8 (CI 23.0 to 41.7% CI 95%). This indicates that the differences between the mammary ligament and the gold standard values will be in ± 10.9 95% of the time. Generally speaking, the researcher must determine whether this interval is close enough to report a match. For this data (for which CAD is ± 5), it is clear that the TDI is too large to conclude that the two devices must be interchangeable. Note that the limits of TDI are similar to those implied by the LoA.

Several different methods have been proposed in the literature to assess the concordance of continuous data, of which the concordance coefficient of concordance [3, 4] and the limits of concordance [5] are the most widespread. . . .


Warning: count(): Parameter must be an array or an object that implements Countable in /homepages/43/d473804928/htdocs/wp-includes/class-wp-comment-query.php on line 399