医学论文中成组t检验P值错误及其原因分析
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摘要
【目的】调查医学论文中成组t检验的P值错误,分析错误原因,并提出相应措施。【方法】选取236种医学期刊,每种期刊选取1项成组t检验,核验其P值,应用χ~2检验、Mantel-Haenszel法、二项式logistic回归分析P值错误。【结果】236项成组t检验中,50项存在P值错误。单因素分析结果显示,核心期刊与非核心期刊相比,P值错误发生率差异具有统计学意义(χ~2=4.871,P=0.027);给出具体P值组与未给出具体P值组相比,P值错误发生率差异具有统计学意义(χ~2=15.440,P<0.0001)。将是否给出具体P值作为混杂因素,比较核心期刊与非核心期刊P值错误发生率,差异无统计学意义(χ~2=2.703,P=0.100)。多因素分析结果显示,是否方差齐(OR值为0.470,95%CI为0.230～0.961)、是否给出具体P值(OR值为5.459,95%CI为2.311～12.895)具有统计学意义。【结论】医学论文成组t检验P值错误较多。为及时发现P值错误,期刊编辑应当重视对统计学方法应用条件的审查,要求作者给出统计描述以及统计推断的具体结果,能够利用简单易学的统计学软件核实P值。
[Purposes]This paper investigates P-value errors in two-sample t-test of medical papers,analyzes the causes of errors,and puts forward the corresponding measures.[Methods]We reviewed 236 two-sample t-test cases from 236 medical journals.The P-value was verified and the P-value errors were analyzed by χ2 test,Mantel-Haenszel method and binomial logistic regression.[Findings]Among the 236 cases,50 cases have P-value errors.The univariate analysis shows that there is a significant difference between core journals and non-core journals in incidence of P-value errors(χ2 = 4.871,P = 0.027),and there is a significant difference between cases with concrete P-value and cases without concrete P-value in incidence of P-value errors(χ2 = 15.440,P< 0.0001).When we regard whether the concrete P-value is described as the confounding factor,no significant difference in the incidence of P-value errors is found between core journals and non-core journals(χ2 = 2.703,P = 0.100).The multivariate analysis shows that whether the variance is equal(OR= 0.470,95%CI:0.230-0.961) and whether the concrete P-value is described(OR= 5.459,95%CI:2.311-12.895) are significant variables.[Conclusions]There is a high incidence of P-value errors in two-sample t-test of medical papers.In order to discover the P-value errors in time,editors should pay attention to the examination of the application conditions of statistical methods,ask the authors to give statistical description and statistical inference result,and verify P-value by simple statistical software.
[Purposes]This paper investigates P-value errors in two-sample t-test of medical papers,analyzes the causes of errors,and puts forward the corresponding measures.[Methods]We reviewed 236 two-sample t-test cases from 236 medical journals.The P-value was verified and the P-value errors were analyzed by χ2 test,Mantel-Haenszel method and binomial logistic regression.[Findings]Among the 236 cases,50 cases have P-value errors.The univariate analysis shows that there is a significant difference between core journals and non-core journals in incidence of P-value errors(χ2 = 4.871,P = 0.027),and there is a significant difference between cases with concrete P-value and cases without concrete P-value in incidence of P-value errors(χ2 = 15.440,P< 0.0001).When we regard whether the concrete P-value is described as the confounding factor,no significant difference in the incidence of P-value errors is found between core journals and non-core journals(χ2 = 2.703,P = 0.100).The multivariate analysis shows that whether the variance is equal(OR= 0.470,95%CI:0.230-0.961) and whether the concrete P-value is described(OR= 5.459,95%CI:2.311-12.895) are significant variables.[Conclusions]There is a high incidence of P-value errors in two-sample t-test of medical papers.In order to discover the P-value errors in time,editors should pay attention to the examination of the application conditions of statistical methods,ask the authors to give statistical description and statistical inference result,and verify P-value by simple statistical software.
引文
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[14]接雅俐,陈汐敏,顾璟,等.医学论著统计学报告水平评价量表的制作与初步应用[J].中国科技期刊研究,2012,23(6):982-987.
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[19]陈攀,冯留顺,潘洁,等.CA199和总胆红素水平在胆管疾病应用中的临床分析[J].医药论坛杂志,2018,39(2):62-64.
[20]张军锋,董海原.医学论文审稿中常见的统计学错误:定量资料统计方法的误用分析[J].中国药物与临床,2017,17(10):1558-1560.
[21]周英智,靳光华.利用文中数据识别统计学错误[J].编辑学报,2016,28(1):29-31.
[22]《中华神经创伤外科电子杂志》编辑部.中华医学会系列杂志对来稿中统计学处理的有关要求[J].中华神经创伤外科电子杂志,2018,4(1):28.
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[24]冯思仪,程兰.痛经的精神心理因素探讨[J].暨南大学学报(自然科学与医学版),2017,38(5):437-442.
[2]马莉,高贵现.《山东医药》杂志常见统计学错误及分析[J].编辑学报,2016,28(1):32-34.
[3]陈姗姗,孙琴.学术不端论文的几大隐性特征及其辅助鉴别方法---以医学科研论文为例[J].湖北师范大学学报(自然科学版),2018,38(3):72-76.
[4]陈文娟,汤雷,马莉.医学期刊常见t检验应用错误及案例分析[J].编辑学报,2016,28(3):237-239.
[5]陈景景,谭晓蕾,徐晓静.护理期刊来稿常见统计学问题及其对策分析[J].科技与出版,2017(2):87-91.
[6]刘静.统计学方法的正确使用问题(一)[J].心肺血管病杂志,2017,36(1):76.
[7]田云鹏,陈丽.医学论文中常见统计学错误例析[J].中华全科医学,2017,15(10):1791-1794.
[8]高永,张中文,石德文,等.基于Excel的统计分析系统在期刊编辑部审稿中的应用[J].编辑学报,2013,25(5):478-481.
[9]潘洪秀,朱晓文,季方茹,等.右美托咪定联合芬太尼对高血压脑出血患者术后脑糖氧代谢及Toll样受体表达的影响[J].中国老年保健医学,2018,16(1):23-27.
[10]中国科学技术信息研究所.2017年版中国科技期刊引证报告(核心版)[M].北京:科学技术文献出版社,2017.
[11]夏成锋,林江娇.2007-2013年中国科技期刊主要计量指标统计分析[J].中国科技期刊研究,2016,27(8):900-903.
[12]袁丽霞,陈雯,黄明睿.动物科技类期刊补白的统计与分析[J].编辑学报,2014,26(6):550-552.
[13]冉明会.医学期刊编辑应重视摘要中统计学著录问题的审编[J].编辑学报,2014,26(3):238-240.
[14]接雅俐,陈汐敏,顾璟,等.医学论著统计学报告水平评价量表的制作与初步应用[J].中国科技期刊研究,2012,23(6):982-987.
[15]孙振球,徐勇勇.医学统计学[M].4版.北京:人民卫生出版社,2014:37.
[16]吴艳妮,周春兰,江霞,等.国内护理学统计源期刊论文中报告精确P值常见错误:P=0.000[J].编辑学报,2016,28(2):133-134.
[17]冯国双,罗凤基.医学案例统计分析与SAS应用[M].北京:北京大学医学出版社,2011:55.
[18]姜春霞.论医学期刊编辑的统计学审核[J].中国科技期刊研究,2014,25(6):782-784.
[19]陈攀,冯留顺,潘洁,等.CA199和总胆红素水平在胆管疾病应用中的临床分析[J].医药论坛杂志,2018,39(2):62-64.
[20]张军锋,董海原.医学论文审稿中常见的统计学错误:定量资料统计方法的误用分析[J].中国药物与临床,2017,17(10):1558-1560.
[21]周英智,靳光华.利用文中数据识别统计学错误[J].编辑学报,2016,28(1):29-31.
[22]《中华神经创伤外科电子杂志》编辑部.中华医学会系列杂志对来稿中统计学处理的有关要求[J].中华神经创伤外科电子杂志,2018,4(1):28.
[23]《郑州大学学报(医学版)》投稿指南[EB/OL].[2018-05-03].http://jms.zzu.edu.cn/Corp/fixed.aspx?id=40.
[24]冯思仪,程兰.痛经的精神心理因素探讨[J].暨南大学学报(自然科学与医学版),2017,38(5):437-442.