HOW TO USE RIDIT ANALYSIS
HOW TO USE RIDIT ANALYSIS
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DOI：
10.2307/2527727
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发表时间：
1958-01-01
期刊：
影响因子：
1.9
通讯作者：
BROSS, IDJ
中科院分区：
文献类型：
--
作者：
BROSS, IDJ
在生物和行为科学的许多科学研究中，反应变量处于二分法分类和精确测量系统之间的“边界”。有时响应变量是主观量表（例如“轻微”、“中度”、“严重”），其他时候响应变量是数值，但测量系统严重依赖于方案的细节。这些“边界”响应变量可能无法通过两种传统统计技术（即卡方和t检验）进行充分分析。在这种情况下，ridit分析成为两个传统家庭之间“缺失的一环”。在ridit分析中，一个特定类别的个体被选为“已识别分布”，其他系列被认为是相对于这个已识别分布的。给定类别的ridit只是较小类别中个人的比例加上该类别本身中个人比例的一半。一旦转换完成，数据就可以沿着通常的t检验系列进行分析。ridit变换的使用说明了从汽车碰撞损伤的研究数据。
In many scientific studies in the biological and behavioral sciences the response variables fall in the "borderland" between dichotomous classifications and refined measurement systems. Sometimes the response variable is a subjective scale (e.g. "minor", "moderate", "severe") and other times the response variable is numerical but the measurement system is heavily dependent upon details of protocol. These "borderland" response variables may not be adequately analyzed by either of the two traditional families of statistical techniques (i.e. the chi-square and t-test families). In this situation ridit analysis serves as a "missing link" between the two traditional families. In ridit analysis a specified class of individuals is chosen as the "identified distribution" and the other series are considered relative to this identified distribution. The ridit for a given category is simply the proportion of individuals in the lesser categories plus one half of the proportion of individuals in the category itself. Once the transformation has been made the data may be analyzed along the lines of the usual t-test families. The use of the ridit transformation is illustrated on data from a study of automotive crash injuries.