Bland Altman Statistical Methods For Assessing Agreement

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Stevens NT, Steiner SH, MacKay RJ. Evaluation of the agreement between two measurement systems: an alternative to the limits of the agreement`s approach. Med Res Stat Methods. 2017;26 (6):2487-504. Barnhart HX, Haber M, Kosinski AS. Evaluation of the individual agreement. J Biopharm Stat. 2007;17:697-719. Roy A.

Application of a linear model of mixed effects to assess the agreement between two methods with replicated observations. J Biopharm Stat. 2009;19 (1):150-73. Choudhary PK. A consistent approach to non-parametric evaluation of matches in comparative method studies. Int J Biostat. 2010;6(1). Article 19. Bland JM, DG Altman. Agreement between measurement methods with multiple observations per person. J Biopharm Stat. 2007;17(4):571-82.

In the case of repeated measurements, the application of standard data compliance limits leads to narrow limit values because they do not take into account the reduction in variability resulting from working with the measured average values. In this case, we must use a specially adapted version of the boundaries of the agreement, for which several methods are available. Bland and Altman first described an ANOVA method with fixed effects to extend the loA method to repeated measurements [20], and this method is briefly described in complementary materials. Hamilton C, Stamey JD. Use a predictive approach to assess the consistency between two measures on an ongoing basis. J Clin Monit Computit. 2009;23 (5):311-4. Five different methods of evaluating the agreement were compared in the same environment to facilitate understanding and promote the practical use of several chord methods. Although there are similarities between methods, each method has its own strengths and weaknesses, which are important for researchers to be aware of them. We propose that researchers consider using the coverage probability method in addition to a graphic representation of raw data in method comparison studies. In the event of disagreement between devices, it is important to go beyond the overall indices of the summary agreement and to consider the underlying causes. The graphic summary of the data and the study of the parameters of the model can be useful for this purpose.

Studies of the agreement examine the distance between values measured by different devices or observers that measure the same amount. If the values generated by each device are close to each other most of the time, so there is no practical difference between the device used, we come to the conclusion that the devices agree. An example of an agreement study is to determine the extent to which two observers using the same instrument generate similar surveys. A second example is determining the importance of how a questionnaire is served when it is provided on the same day to the same group of participants. Chen and his colleagues, for example, examined whether two different versions of the Epworth Sleepiness scale (electronic and paper) produced the same values when both patients were administered with obstructive sleep apnea on the same day [1]. Given that the differences between electronic and paper versions were mostly within ± 4, this was considered an acceptable agreement in this case [1]. The agreement contains both precision and precision: the discord between the devices may be due to a systematic distortion of one device in relation to the other, or if at least one of the devices is imprecise [2]. Myles PS, Cui J. Using the Bland-Altman method to measure agreement with repeated measurements.

Br J Anaesth. 2007;99(3):309–11. For both the boundaries of the agreement and the TDI methods, it is important to remember that the calculated limit values are only estimates (as the CCC is a point estimate) and are therefore uncertain in the actual values of these limit values [44]. Different samples of the total population may produce different limit values and another DTT. Particularly for reduced sample sizes, the match limits observed may be far from «true» match limits due to finite sampling distortions.

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