where t (b, -z p N1/2) is a non-central t distribution with degrees of freedom and non-centrality parameters -z p N1/2 (Johnson, Kotz, Balakrishnan [14], Chapter 31). As a result, T-provides an essential quantity for building confidence intervals of ordinary percentiles. A one-sided confidence interval of 100 (1 – α) is expressed in “” ()) l, ∞” and the lower confidence limit is to compare the measurement systems using the Bland Altman method, the differences between the different measurements of the two different measurement systems are calculated, and then the average and the standard deviation are calculated. The 95% of “agreement limits” are calculated as the average of the two values minus and plus 1.96 standard deviation. This 95 per cent agreement limit should include the difference between the two measurement systems for 95 per cent of future measurement pairs. The simple 95% limits of the agreement method are based on the assumption that the average value and standard deviation of differences are constant, i.e. they do not depend on the size of the measurement. In our original documents, we described the usual situation where the standard deviation is proportional to size, and described a method using a logarithmic transformation of the data. In our 1999 review paper (Bland and Altman 1999), we described a method to avoid any relationship between the average and the SD of the differences and magnitude of the measurement. (It was Doug Altman`s idea, I can`t take recognition.) Lin LI, Hedayat AS, Sinha B, et al. Statistical methods for evaluating the agreement: models, problems and instruments. J Am Stat Assoc.

2002:97:257-70. 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 to vary the property to be determined 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. The 95% limit values are then set at each average ±1,96SD. To specify the sample size, use t0.05.N1 instead of 1.96. The pearson values r from 0 to 1.0 are a positive correlation; 1.0 is a perfect correlation. Laboratory experts use the Pearson formula to evaluate the range of two values such as tests or to compare assay results with the standard or potassium results previously assigned. Most operators set a r value of 0.975 (or r2 of 0.95) as a lower correlation limit; A pearson value r less than 0.975 is considered zero because it indicates unacceptable variability in the reference method.

Note that the lower and higher confidence limits of a bilateral confidence interval of 100 (1 – α) per cent correspond to the lower and higher confidence limits of the 100 (1 – α/ 2) % of unilateral or lower confidence intervals. In order to demonstrate the potential disadvantage of approximate interval procedures between Chakraborti and Li [24], Bland and Altman [2], a simulation study was conducted to assess the coverage of their one- and two-sided confidence intervals. Although the approximate Bland and Altman interval method [2] in Carkeet and Goh [20] was studied from a different perspective, the particular method of completeness and the intent to report additional properties that had not previously been notified is included in the following assessment.