# The 95 Limits Of Agreement

Choudhary PK, Nagaraja HN. Measuring compliance in method comparison studies – an audit. In: Balakrishnan N, Kannan N, Nagaraja HN, editor. Investment and selection progress, multiple comparisons and reliability. Boston: Birkhauser; 2004. 215-44. Bland and Altman indicate that two methods developed to measure the same parameter (or property) should have a good correlation when a group of samples is selected so that the property to be determined varies considerably. Therefore, a high correlation for two methods of measuring the same property could in itself be only a sign that a widely used sample has been chosen. A high correlation does not necessarily mean that there is a good agreement between the two methods.

Odeh RE, Owen DB. Tables of normal tolerance limits, sampling plans and sampling. New York: Marcel Dekker; Although the practical implementation of the exact Method of the Carkeet Interval [19] is well illustrated, the explanation of the differences between the exact and approximate methods has mainly focused on the relative size and symmetrical/asymmetric limits of the resulting confidence limits. On the other hand, Bland-Altman`s 95% agreement limits are generally considered to be related to the measurement of compliance in comparing methods. Carkeet [19] and Carkeet and Goh [20] therefore focused on comparing approximate confidence intervals for the upper and lower limits of torque chords and tolerance intervals on both sides for normal distribution. Therefore, the particular benefit of precise interval procedures and the ability to limit approximate confidence intervals for each upper and lower limit of the Carkeet [19] and De Carkeet and Goh [20] agreement were not fully discussed. It is practical to conduct a detailed assessment of the accuracy and discrepancy between exact and approximate interval methods for an individual match limit in a multitude of model configurations. The problem of achieving a uniform confidence interval to cover both limitations of the agreement at the same time is more involved and an in-depth discussion on this subject goes beyond the scope of this study.

Bland JM, Altman D. Statistical methods to assess the consistency between two methods of clinical measurement. Lancet. 1986;327:307–10. The delimitation shows the theoretical correlations between the different shooting sizes in order to obtain precise confidence intervals. In addition, seemingly accurate methods of reconciliation, which are also far removed from the main treasures, have unwanted confidence limits. It is found that the optimal sample size has a median or medium minimum and increases when the percentile approaches the extremes. In particular, 10,000 iteration simulation studies were conducted to calculate the probability of simulated coverage of accurate and approximate confidence intervals for percentiles in a standard distribution N (0, 1). The sample size is six different sizes: No.

10, 20, 30, 50, 100 and 200. In addition, eight probabilities of percentiles are studied: p – 0.025, 0.05, 0.10, 0.20, 0.80, 0.90, 0.95 and 0.975. For each replication, the lower and upper confidence limits () (“widehat” (Uptheta) L , “”uptheta” U, DIE A/ (“widehat” (“breithat” – “uptheta”) AL, “widehat” and “uptheta” and “breithat”) were calculated to establish unilateral confidence intervals of 95 and 97.5%, as well as reciprocal confidence intervals of 90 and 95%.