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| 医学科研中样本资料的综合评价问题 | |
| 引用本文： | 王一任,孙振球,谢江波,曾小敏.医学科研中样本资料的综合评价问题[J].中南大学学报(医学版),2014,39(4):416-422. |
| 作者姓名： | 王一任 孙振球 谢江波 曾小敏 |
| 作者单位： | 中南大学 1. 公共卫生学院，长沙 410078；2. 湘雅医学院附属肿瘤医院，长沙 410013 |
| 基金项目： | 湖南省学位与研究生教育教学改革研究项目(JG2012B005)；中南大学研究生教学改革项目(2012jg20)；中南大学 中央高校基本科研业务费专项资金项目(ZYZX10QN54)。 This work was supported by the Degree and Postgraduate Research Project of Education Reform of Hunan Province (JG2012B005), Degree and Postgraduate Research Project of Education Reform of Central South University (2012jg20) and the Fundamental Research Funds for the Central Universities (ZYZX10QN54), P. R. China. |
| 摘 要： | 综合评价方法一般是对总体资料(特定空间和时间)进行评价。在某些特殊情形下，需要对样本资料进行 评价，那么在综合排序时有必要考虑抽样误差对排序结果的影响。然而目前综合评价方法对评价结果只能描述，不 能进行统计推断，因此存在着抽样误差的估计问题。本文利用Monte Carlo模拟方法求解排序结果的概率并给出Matlab 程序，基于模拟结果，将综合评价的传统“绝对结论”改为“概率结论”，提出了一种新的综合评价结果排序的方 法及新的结果分档法。 |
| 关 键 词： | 抽样误差 综合评价 Monte Carlo模拟 概率结论 |
Comprehensive evaluation of sample data in medical research |
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| WANG Yiren,SUN Zhenqiu,XIE Jiangbo,ZENG Xiaomin.Comprehensive evaluation of sample data in medical research[J].Journal of Central South University (Medical Sciences)Journal of Central South University (Medical Sciences),2014,39(4):416-422. | |
| Authors: | WANG Yiren SUN Zhenqiu XIE Jiangbo ZENG Xiaomin |
| Institution: | 1. School of Public Health, Central South University; Changsha 410078; 2. Affiliated Tumor Hospital, School of Xiangya Medicine, Central South University, Changsha 410013, China |
| Abstract: | Comprehensive evaluation methods are generally used to assess the population data. When we need to estimate the sample data in special situations, the impacts brought by the sampling error should be considered. Due to lack of the accurate measurement for the sensitivity and stability in the comprehensive evaluation methods, sampling errors usually cannot be estimated in the sampling research. Monte Carlo simulation was used in this article to solve the probability of the ordering results, and the matlab programs were presented. Based on the simulated results, we change the conventional “absolute conclusion” of comprehensive evaluation methods to “probability results” for the sample data, and put forward a new sorting and ranking method for the results of comprehensive evaluation. |
| Keywords: | sampling error comprehensive evaluation Monte Carlo simulation probability result |
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