Hypothesis testing III: Counts and medians

被引:41
作者
Applegate, KE
Tello, R
Ying, J
机构
[1] Boston Univ, Dept Radiol, Boston, MA 02118 USA
[2] James Whitcomb Riley Hosp Children, Dept Radiol, Indianapolis, IN 46202 USA
[3] Indiana Univ, Sch Med, Dept Radiol, Indianapolis, IN 46202 USA
[4] Indiana Univ, Sch Med, Dept Biostat, Indianapolis, IN 46202 USA
关键词
statistical analysis;
D O I
10.1148/radiol.2283021330
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Radiology research involves comparisons that deal with the presence or absence of various imaging signs and the accuracy of a diagnosis. In this article, the authors describe the statistical tests that should be used when the data are not distributed normally or when they are categorical variables. These nonparametric tests are used to analyze a 2x2 contingency table of categorical data. The tests include the chi(2) test, Fisher exact test, and McNemar test. When the data are continuous, different nonparametric tests are used to compare paired samples, such as the Mann-Whitney U test (equivalent to the Wilcoxon rank sum test), the Wilcoxon signed rank test, and the sign test. These nonparametric tests are considered alternatives to the parametric t tests, especially in circumstances in which the assumptions of t tests are not valid. For radiologists to properly weigh the evidence in the literature, they must have a basic understanding of the purpose, assumptions, and limitations of each of these statistical tests. (C) RSNA, 2003.
引用
收藏
页码:603 / 608
页数:6
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