de Vet H C, Beurskens A J
Vakgroep Epidemiologie, Universiteit Maastricht.
Ned Tijdschr Geneeskd. 1998 Sep 12;142(37):2040-3.
Reproducibility measurements are important for a proper interpretation of medical data. Kappa is the most adequate measure for categorical variables. Kappa adjusts the observed agreement for chance agreement. The interpretation of kappa is rather difficult. The kappa value is influenced by the number of categories used for classification and the prevalence of scores of the observers. For continuous variables the Pearson correlation coefficient can be used, keeping in mind its ignoring systematic errors and its dependence on the heterogeneity of the data. Another method to assess reproducibility for continuous variables is the method of limits of agreement. This method distinguishes systematic and random errors, and quantifies the differences in the dimension of the measurements. In general, the interpretation of the various measures of agreement is helped by a visual presentation of the data in a table or figure.
重复性测量对于正确解读医学数据很重要。卡帕系数是用于分类变量的最合适指标。卡帕系数会对观察到的一致性进行机遇一致性调整。卡帕系数的解读相当困难。卡帕值受分类所用类别数量以及观察者评分患病率的影响。对于连续变量,可以使用皮尔逊相关系数,但要记住它会忽略系统误差且依赖于数据的异质性。评估连续变量重复性的另一种方法是一致性界限法。该方法能区分系统误差和随机误差,并对测量维度上的差异进行量化。一般来说,通过以表格或图形形式直观呈现数据,有助于对各种一致性指标进行解读。