我的问题是关于这个虚拟数据的。我想测试一下一起考虑的三个方法(V1,V2和V3)之间是否存在显着差异。在R And中,测试v1的平均值是否与V2显着不同。
id <- c(1,2,3,4,5,6,7,8,9,10)
V1<- c(50, 42, 58, 56, 25, 85, 12, 23, 89, 52)
V2<- c(65, 63, 52, 45, 89, 58, 74, 51, 26, 25)
V3<- c(68, 95, 62, 14, 12, 25, 48, 56, 32, 57)
sex <- c("F","F","F","F","F","M","F","F","M","M")
data<- data.frame(id,V1,V2,V3,sex)
我尝试使用方差分析,但未成功
答案 0 :(得分:0)
如果要使用anova(),则需要使用lm()包装公式。
id <- c(1,2,3,4,5,6,7,8,9,10)
V1<- c(50, 42, 58, 56, 25, 85, 12, 23, 89, 52)
V2<- c(65, 63, 52, 45, 89, 58, 74, 51, 26, 25)
V3<- c(68, 95, 62, 14, 12, 25, 48, 56, 32, 57)
sex <- c("F","F","F","F","F","M","F","F","M","M")
data<- data.frame(id,V1,V2,V3,sex)
anova(lm(id ~ V1 + V2 + V3, data = data))
Analysis of Variance Table
Response: id
Df Sum Sq Mean Sq F value Pr(>F)
V1 1 0.438 0.4382 0.0751 0.79330
V2 1 29.750 29.7497 5.0959 0.06478 .
V3 1 17.285 17.2846 2.9607 0.13610
Residuals 6 35.028 5.8379
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1