==== 二因素方差分析过程 Two-factor ANOVA procedure ==== ---- === 1、陈述假设stated hypothesis === 二因素方差分析的假设有三: Three assumptions were made for the two-factor ANOVA: - 因素A的主效应(Main effect of factor A):虚无假设(null hypothesis)为H0: μA1A2=... - 因素B的主效应(Main effect of factor B):虚无假设(null hypothesis)为H0: μB1B2=... - 因素A和因素B的交互作用:交互作用的虚无假设通常用文字来表示,即因素A(B)对因变量的影响不因因素B(A)的变化而变化。 * Interaction of factor A and factor B:The null hypothesis for the interaction is usually stated in words, i.e., the effect of factor A(B) on the dependent variable does not change as a result of changes in factor B(A). ---- === 2、计算相关统计量 Calculation of relevant statistics === * 自由度的计算 Calculation of degrees of freedom{{ ::自由度1.jpg?nolink&300 |}} {{ ::自由度2.jpg?nolink&300 |}} {{ ::自由度3.jpg?nolink&300 |}} * 根据公式计算所需的统计量 Calculation of the required statistic according to the formula {{ ::ss1.jpg?nolink&200 |}} {{ ::ss2.jpg?nolink&400 |}} {{ :ss3.jpg?nolink&400 |}} * 确定显著性水平α Determination of the significance level α * 确定临界F值 Determination of critical F-value //这里临界F值有三个,分别是FcritA、FcritB、FcritA×B。// //Here the critical F-values are three, which areFcritA、FcritB、FcritA×B.// ---- === 3、计算F统计量 Calculating the F-statistic === * 根据前面算出的各个值作出如下所示的方差分析表 The ANOVA table shown below was made based on the individual values calculated earlier: {{ ::方差分析表2_2_.jpg?nolink&400 |}} * 画出交互作用图 Draw the interaction diagram ---- === 4、得出检验结论 Drawing test conclusions === 根据算出的各个F值与相应F临界值的比较结果决定是否接受虚无假设。 The decision to accept the null hypothesis is based on the results of the comparison of the calculated individual F values with the corresponding F critical values. 注意当因素之间的交互效应显著时要进行简单主效应分析,即确定一个因素水平,对另一因素的不同水平作单因素ANOVA。 Note that when the interaction effect between factors is significant a simple main effects analysis is performed, i.e., a factor level is determined and a one-factor ANOVA is done for a different level of another factor.