The Bland-Altman diagram shows four types of data errors. These types are systematic errors (1) (average shift), (2) proportional error (trend), (3) inconsistent variability and (4) excessive or irregular variability. The SEM (standard measurement defect) indicates, for example.B. the amount of measurement errors and how a standard error (s) can be used to calculate a confidence interval in a palpated value. In general, we can use the SEM with a z table to calculate confidence intervals for a measurement. So if we want a 95% confidence interval when measuring, we can look at a z table to find the z value that corresponds to a probability of 2.5% (z-1.96). Thus, our confidence interval of 95% – measures – 1.96 SEM. Intercept measures the constant systematic errors (or bias, in the mouth of the laboratory), a constant difference between the new test and the reference test, regardless of the size of the test result. A lab manager may opt for a new test with constant systematic errors, but he must change the published IR. Figure 27.31. Bland-Altman diagram with 95% confidence limits with a gradual increase in differences and heterosis.
Control panel on the left: Traditional diagram with average (dotted line), best fit line and 95% confidence limits. Right panel: Allowance for heteroskedasticity, with better adaptation to data. Compliance limitations include both systematic errors (bias) and random errors (precision) and provide a useful measure for comparing likely differences between different results measured using two methods. If one method is a reference method, compliance limits can be used as a measure of the total error of a measurement method (Krouwer, 2002). If you use the coefficient of variation instead of the typical uns formatted error, it is useful to present all changes in the average value between tests as percentage changes. In our example of body weight, the movement of the average is -0.9 kg -1.2%. Percentage changes and coefficient of variation can be inferred by analyzing the variables processed in the log. Details can be found on the page for calculations for details. Exercise 15.5. Figure 15.3 shows preoperative levels compared to postoperative plasma silicon levels in the DB5 breast implant. Interpret the results of Bland Altman`s plot.
Figure 15.2. A Bland-Altman diagram from Clinic 104 in relation to the DB13 laboratory data. By the way, I don`t know what the intraclass means. I guess the intra refers to how typical errors go into calculating correlation. The limit values ±1.96 × SD difference are then on either side of the predicted value. The 95% confidence limit diagram is shown in Figure 27.31, the limit values are shown by calculating the difference of the SD at two average values and linking them by a straight line. Linear regression and the pearson correlation coefficient are essential tests of accuracy and performance; However, both are influenced by dispersion. The Bland-Altman Difference Chart, also known as the Tukey Average Difference Diagram, provides a graphic representation of the concordance between two assays.20 Just as for the t test, Pearson correlation and linear regression, coupled assay results are represented in automated table columns. This formula is applied: Figure 15.2 shows a Bland-Altman diagram of the 104 clinics compared to laboratory data on warfarin-INR values in DB13.