Armstrong R A, Eperjesi F, Gilmartin B
Vision Sciences, Aston University, Birmingham, UK.
Ophthalmic Physiol Opt. 2002 May;22(3):248-56. doi: 10.1046/j.1475-1313.2002.00020.x.
Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered.
方差分析（ANOVA）是分析实验数据最有效的方法。方差分析是一种相当复杂和微妙的方法，有许多不同的变体，每种变体适用于特定的实验情境。因此，有可能将错误类型的方差分析应用于数据，从而从实验中得出错误的结论。本文回顾了验光临床实验中最可能出现的方差分析类型，包括单因素方差分析（“固定”和“随机效应”模型）、随机区组设计中的双因素方差分析、三因素方差分析以及析因实验设计（包括“裂区设计”和“重复测量”等变体）。对于每种方差分析，描述了适当的实验设计，制定了统计模型，并讨论了每种设计类型的优缺点。此外，还考虑了不符合统计模型的问题以及重复次数的确定。
