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Sample Size for Assessing Agreement between Two Methods of Measurement by Bland-Altman Method.

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TLDR
In this article, the authors proposed a new method of sample size estimation for Bland-Altman agreement assessment, which is based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit.
Abstract
The Bland-Altman method has been widely used for assessing agreement between two methods of measurement. However, it remains unsolved about sample size estimation. We propose a new method of sample size estimation for Bland-Altman agreement assessment. According to the Bland-Altman method, the conclusion on agreement is made based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit. Under the theory of statistical inference, the formulae of sample size estimation are derived, which depended on the pre-determined level of α, β, the mean and the standard deviation of differences between two measurements, and the predefined limits. With this new method, the sample sizes are calculated under different parameter settings which occur frequently in method comparison studies, and Monte-Carlo simulation is used to obtain the corresponding powers. The results of Monte-Carlo simulation showed that the achieved powers could coincide with the pre-determined level of powers, thus validating the correctness of the method. The method of sample size estimation can be applied in the Bland-Altman method to assess agreement between two methods of measurement.

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Citations
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Journal ArticleDOI

Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies.

TL;DR: In this article, the importance of sample size and its relationship to effect size (ES) and statistical significance is discussed. But, there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion, and use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies.
Journal ArticleDOI

Reporting Standards for a Bland-Altman Agreement Analysis: A Review of Methodological Reviews.

TL;DR: The present study aimed to identify the most comprehensive and appropriate list of items for such an analysis, identifying 13 key items for reporting Bland–Altman agreement analyses.
References
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Journal ArticleDOI

Statistical methods for assessing agreement between two methods of clinical measurement.

TL;DR: An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
Journal ArticleDOI

Measuring agreement in method comparison studies

TL;DR: The 95% limits of agreement, estimated by mean difference 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie.
Journal ArticleDOI

Research guidelines for the Delphi survey technique.

TL;DR: This paper aims to provide an understanding of the preparation, action steps and difficulties that are inherent within the Delphi method, used systematically and rigorously, to contribute significantly to broadening knowledge within the nursing profession.
Journal ArticleDOI

Applying the right statistics: analyses of measurement studies

TL;DR: The problems of some applications of correlation and regression methods to these studies are described, using recent examples from this literature, and the 95% limits of agreement approach and a similar, appropriate, regression technique are described.
Book

Statistical Intervals: A Guide for Practitioners

TL;DR: In this article, a detailed exposition of statistical intervals and emphasizes applications in industry is presented. But the discussion differentiates at an elementary level among different kinds of statistical interval and gives instruction with numerous examples and simple math on how to construct such intervals from sample data, including confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value and prediction intervals to include observation in a future sample.
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