[Development of Sample Size Formulas for Least Square Regression-Based Consistency Evaluation of Quantitative Indicators].

Q4 Medicine
Fei-Long Chen, Miao Yu, Tao Xu
{"title":"[Development of Sample Size Formulas for Least Square Regression-Based Consistency Evaluation of Quantitative Indicators].","authors":"Fei-Long Chen, Miao Yu, Tao Xu","doi":"10.3881/j.issn.1000-503X.15523","DOIUrl":null,"url":null,"abstract":"<p><p>Objective To develop and verify the sample size formulas for quantitative data consistency evaluation based on the least square regression method. Methods According to the principle of least square regression-based quantitative consistency evaluation,statistical inference,and formula derivation,we developed the formulas for calculating sample size based on regression constant and regression coefficient.Furthermore,the accuracy of the formulas was verified by the data of three examples,and the results were compared with those of the sample size formula established based on the Bland-Altman(BA)method. Results The sample size formulas for regression-based quantitative consistency evaluation were deduced,and the accuracy of the formulas was verified by three examples.In addition,the results obtained with this formula had differences compared with those of the sample size formula established based on the BA method.Furthermore,consistent conclusions could be obtained by regression analysis and BA analysis with the sample size calculated with the regression method.However,with the sample size calculated based on the BA method,the consistency conclusion of regression analysis and BA analysis was sometimes not valid. Conclusion A sample size formula for quantitative consistency evaluation based on the regression method was proposed for the first time,which provided methodological support for the research in this field.</p>","PeriodicalId":6919,"journal":{"name":"中国医学科学院学报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国医学科学院学报","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.3881/j.issn.1000-503X.15523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Objective To develop and verify the sample size formulas for quantitative data consistency evaluation based on the least square regression method. Methods According to the principle of least square regression-based quantitative consistency evaluation,statistical inference,and formula derivation,we developed the formulas for calculating sample size based on regression constant and regression coefficient.Furthermore,the accuracy of the formulas was verified by the data of three examples,and the results were compared with those of the sample size formula established based on the Bland-Altman(BA)method. Results The sample size formulas for regression-based quantitative consistency evaluation were deduced,and the accuracy of the formulas was verified by three examples.In addition,the results obtained with this formula had differences compared with those of the sample size formula established based on the BA method.Furthermore,consistent conclusions could be obtained by regression analysis and BA analysis with the sample size calculated with the regression method.However,with the sample size calculated based on the BA method,the consistency conclusion of regression analysis and BA analysis was sometimes not valid. Conclusion A sample size formula for quantitative consistency evaluation based on the regression method was proposed for the first time,which provided methodological support for the research in this field.

[基于最小平方回归的定量指标一致性评价样本量公式的开发]。
目的 建立并验证基于最小二乘法回归的定量数据一致性评价样本量计算公式。方法 根据基于最小二乘法回归的定量一致性评价原理、统计推断和公式推导,建立基于回归常数和回归系数的样本量计算公式,并通过三个实例的数据验证公式的准确性,将结果与基于布兰-阿尔特曼(BA)法建立的样本量计算公式进行比较。结果 推导出了基于回归法的定量一致性评价样本量公式,并通过三个实例验证了该公式的准确性;此外,该公式得出的结果与基于布兰德-阿尔特曼法建立的样本量公式得出的结果存在差异;而且,在使用回归法计算样本量的情况下,回归分析和布兰德-阿尔特曼分析可以得出一致的结论;但是,在使用布兰德-阿尔特曼法计算样本量的情况下,回归分析和布兰德-阿尔特曼分析的一致性结论有时不成立。结论 首次提出了基于回归法的定量一致性评价样本量公式,为该领域的研究提供了方法论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
中国医学科学院学报
中国医学科学院学报 Medicine-Medicine (all)
CiteScore
0.60
自引率
0.00%
发文量
6813
期刊介绍: Acta Academiae Medicinae Sinicae was founded in February 1979. It is a comprehensive medical academic journal published in China and abroad, supervised by the Ministry of Health of the People's Republic of China and sponsored by the Chinese Academy of Medical Sciences and Peking Union Medical College. The journal mainly reports the latest research results, work progress and dynamics in the fields of basic medicine, clinical medicine, pharmacy, preventive medicine, biomedicine, medical teaching and research, aiming to promote the exchange of medical information and improve the academic level of medicine. At present, the journal has been included in 10 famous foreign retrieval systems and their databases [Medline (PubMed online version), Elsevier, EMBASE, CA, WPRIM, ExtraMED, IC, JST, UPD and EBSCO-ASP]; and has been included in important domestic retrieval systems and databases [China Science Citation Database (Documentation and Information Center of the Chinese Academy of Sciences), China Core Journals Overview (Peking University Library), China Science and Technology Paper Statistical Source Database (China Science and Technology Core Journals) (China Institute of Scientific and Technological Information), China Science and Technology Journal Paper and Citation Database (China Institute of Scientific and Technological Information)].
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信