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

IF 1.2 4区 数学 International Journal of Biostatistics Pub Date : 2016-11-01 DOI:10.1515/ijb-2015-0039
Mengfei Lu, Weihua Zhong, Yu-xiu Liu, Hua-zhang Miao, Yong-Chang Li, Mu-Huo Ji
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引用次数: 169

Abstract

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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用Bland - Altman方法评估两种测量方法之间一致性的样本量
摘要:Bland-Altman方法被广泛用于评估两种测量方法之间的一致性。然而,关于样本容量的估计仍然是一个没有解决的问题。本文提出了一种新的Bland-Altman协议评估的样本量估计方法。Bland-Altman方法根据loa置信区间的宽度(一致限)与预定义的临床一致限进行比较,得出一致性结论。在统计推断理论的基础上,导出了基于α、β、两次测量差的均值和标准差以及预先设定的限值的样本量估计公式。该方法对方法比较研究中经常出现的不同参数设置下的样本量进行了计算,并利用蒙特卡罗模拟得到了相应的幂次。蒙特卡罗仿真结果表明,得到的功率与预定的功率水平吻合,从而验证了该方法的正确性。在Bland-Altman方法中,样本量估计方法可用于评估两种测量方法之间的一致性。
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来源期刊
International Journal of Biostatistics
International Journal of Biostatistics Mathematics-Statistics and Probability
CiteScore
2.30
自引率
8.30%
发文量
28
期刊介绍: The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
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