变异数分析(analysis of variance, ANOVA)统计方法，目前已被广泛的应用于各种学术领域。过去国内一些研究者在使用这种统计方法时，习惯采用综合的F考验，如果发现F考验达统计的显著(Statistical significance)则继续进行事后比较(Post hoc Comparison)，若无显著，则告一段落。不可否认的，这种作法对于探究性的研究极为有用M，但有些研究应该使用计画性的比较(Planned comparison)或称事前的比较(Priori comparison)较具科学价值。本文旨在叙述事前比较的意义、重要性、统计方法以及与统计方法有密切关系的错误率的问题，其中包括下列三种统计方法：(1)多重t考验(Multiple t tests)，(2)正交比较(Orthogonal contrasts)，(3)杜纳考验(Dunn's tests)

The analysis of variance (ANOVA) currently enjoys the status of being probably the most uSed (some would say abused) statistical technique in every field of research. In the past, when this procedure was used, from the very begining researchers usually ran an overall F-test. If a significant F value was obtained, what they would have shown was simply that the overall null hypothesis was false and continue to run post hoc comparisons to investigate hypothesis involving means of individual groups or sets of groups. On the other hand, If the overall F value was not significant, then the procedure was brought to an end. While post hoc comparisons are important in actual research, especially for exploring one's data and for getting leads for future research, the method of priori comparisons is perhaps more powerful and of greater scientific value.bThe purposes of this article are : (1) to describe the meanning and importance of priori comparisons and related error rate and (2) to introduce the priori comparison procedures of multiple t test, orthognoal contrasts, and Dunn's test.