沿用经典的测验信度定义,简介了信度与α系数的关系以及繇数的局限。为了推荐替代繇数的信度估计方法,深入讨论了与α系数关系密切的同质性信度和内部一致性信度。在很一般的条件下,证明了α系数和同质性信度都不超过内部一致性信度,后者不超过测验信度,说明内部一致性信度比较接近测验信度。总结出一个测验信度分析流程,说明什么情况下α系数还有参考价值:什么情况下α系数不再适用,应当使用内部一致性信度(文献上也常称为合成信度)。提供了计算同质性信度和内部一致性信度的计算程序,一般的应用工作者可以直接套用。
In the research of psychology and other social sciences, test reliability is often used to reflect measurement stability and consistency. Coefficient α is the most popular indicator of test reliability. Recent years, however, coefficient α was challenged now and again. Is coefficient α still recommended for evaluating test reliability? If not, what should replace it? With the classical concept of reliability, which is defined as the ratio of true variance to observed variance on a test under consideration, we introduced the relationship between test reliability and coefficient α, and the limitations of coefficient α. The concepts closely related to coefficient α were considered. We clearly defined homogeneity reliability and internal consistency reliability. Homogeneity reflects the presence of a general factor, whereas internal consistency relates the presence of common factors (including a general factor and local factors). For unidimensional tests, homogeneity and internal consistency are the same concept. Investigating the relationship between test reliability, coefficient a, homogeneity reliability, and internal consistency reliability, we showed that homogeneity reliability is not larger than internal consistency reliability, and that the latter is not larger than test reliability; coefficient α usually underestimates internal consistency reliability, and the latter is closer to test reliability. For ordinary use, the errors of items in a test are reasonably uncorrelated. Under the assumption that the total score of the test is meaningful, we proposed a guideline for evaluating test reliability. If coefficient a is high enough to be accepted, then the test reliability is also acceptable whether the test is unidimensional or not. In this case, using coefficient a to evaluate test reliability is the first choice. If the coefficient a is not large enough, we should calculate internal consistency reliability which is also known as composite reliability in literatures. If the internal consis