Zou GY. Estimated confidence interval for Bland-Altman limits of compliance with multiple observations per person. Med Res Stat Methods. 2013;22:630. Barnhart HX, Haber MJ, Lin LI. An overview of the assessment of compliance with ongoing measures. J Biopharm Stat. 2007;17(4):529-69. Based on the studies described above, each of the five statistical approaches is summarized in Table 2. Further statistical information on these methods, additional diagnostic diagrams and the R-code used to obtain the results will be provided in all additional documents. To compare respiratory frequencies between chest-band and gold standard devices, naïve estimates of concordance (which do not take into account grouping) were calculated to provide simple and rapid summaries of compliance: Pearson`s correlation coefficient was 0.74 (95% confidence interval (IC) 0, 69 to 0.78), the correlation coefficient was 0.72 (IC 95% 0.67 to 0.76) and simple match limits ranged from 6.40 to 3.19, with an average distortion of 1.61.
For a property to be a necessary condition, it must always be present when the effect is present. Since this is the case, we are interested in examining cases where the effect is present and to learning about the characteristics that exist and are absent under the „possible necessary conditions.“ Obviously, the properties missing if the effect is present cannot be necessary conditions for effect. This method is also generally described in comparative policy as the most diverse conception of the system. Symbolically, the method of concordance can be presented as: John Stuart Mill (1806-1873) was an English philosopher who wrote on a wide range of subjects ranging from language and science to political philosophy. The so-called „mill“ methods are five rules for the search for the causes he has proposed. It has been assumed that some of these rules were in fact discussed by the famous Islamic scientist and philosopher Avicenna (980-1037). Explains sample size determination for trials on the basis of measurement agreements On the other hand, the limitations of the agreement and DDI methods have the advantage of being able to be based on the initial unit of measurement and be compared to a clinically acceptable difference . In the reviews of Barnhart et al.  and Barnhart , the authors point out that it is possible for the LoA to have 95% of the differences in the clinically acceptable difference, but not to reach an agreement (for example, if one of the limits is outside the CAD). This can happen in the event of distorted data or another error in accepting normality. We agree that this may be a problem in the search for loA interpretation and that it is particularly important to review the assumptions in the implementation of loA.
However, we believe that the ability of the methodology (and in particular the Bland-Altman plot) to highlight relative average distortions, patterns in the data and therefore sources of differences of opinion, is valuable; and that the simple calculation of a TDI or CP synthesis index can mask this detail. Therefore, if the TDI or CP is calculated, we recommend that a Bland-Altman style diagram of coupled differences between devices should also be constructed relative to the average, which shows gross average distortion and CAD, and suggest that this provides a solid way to assess match. In particular, outliers or slates in the data can be easily studied in relation to CAD.