Bland and Altman indicate that two measurement 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. Researchers studied the agreement between primary care and ambulatory monitoring during the day for blood pressure measurement. The study subjects were patients with newly diagnosed high blood pressure or borderline blood pressure, or patients receiving treatment for hypertension but having poor control. A total of 179 patients were recruited from three general practices and eight physicians participated in blood pressure measurement. Ambulatory monitoring per day was conducted between 0700 and 2300 hours.1 Bland-Altman plots were also used to investigate a possible correlation between the differences between the measurements and the actual value (i.e. proportional distortion). The existence of proportional distortion indicates that the methods do not uniformly correspond to the range of measures (i.e., the limits of compliance depend on the actual measure). To formally assess this relationship, the difference between methods should be reduced to the average of the two methods. If a relationship between differences and actual value has been identified (i.e.
a significant slope of the regression line), 95% regression-based agreements should be indicated.  The tutorial discusses the relationship between methods, estimating average distortion and match limits, understanding the importance of repeatability, using replication measures, managing a relationship between difference and size, transforming measures to remove a relationship, estimating compliance limits based on regression, and estimating non-parametric compliance limits. c) To infer the limits of compliance on the Bland-Altman diagram, differences in systolic blood pressure measurements were considered normal a) Significant correlation (r-0.46; P<0.05) between systolic blood pressure measurements shows a good match between primary care and ambulatory monitoring during the day Find out how to assess the consistency between two measurement methods with the analysis for Microsoft Excel. A significant correlation was established between systolic blood pressure as measured by the family physician and ambulatory systolic pressure per day (r-0.46). P<0.05). Physician measurements exceeded the measurements obtained through outpatient monitoring by an average of 18.9 mm Hg. The Bland-Altman method was used to present the difference in systolic blood pressure for each patient (GP minus outpatient daily monitoring) with the average of both measures (fig. 1⇓). Compliance limits are indicated by broken red lines, i.e.
the two standard deviations of measurement differences on both sides of the average difference. A Bland-Altman plot (differential diagram) in analytical chemistry or biomedicine is a method of data representation used in the analysis of the agreement between two different trials. It is identical to a tube of average difference Tukey, the name under which it is known in other areas, but it was popularized in the medical statistics of J. Martin Bland and Douglas G. Altman.   Consider an example of N-Displaystyle n (z.B objects of unknown volume).