我试图找到包含以下 6 个因素的变量 stim_ending_t 之间的平均差异:1、1.5、2、2.5、3、3.5
您可以在此处访问 df
stim_ending_t visbility soundvolume Opening_text m sd coefVar
<dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 1 0 0 Now focus on the Image 1.70 1.14 0.670
2 1 0 0 Now focus on the Sound 1.57 0.794 0.504
3 1 0 1 Now focus on the Image 1.55 1.09 0.701
4 1 0 1 Now focus on the Sound 1.77 0.953 0.540
5 1 1 0 Now focus on the Image 1.38 0.859 0.621
6 1 1 0 Now focus on the Sound 1.59 0.706 0.444
7 1.5 0 0 Now focus on the Image 1.86 0.718 0.387
8 1.5 0 0 Now focus on the Sound 2.04 0.713 0.350
9 1.5 0 1 Now focus on the Image 1.93 1.00 0.520
10 1.5 0 1 Now focus on the Sound 2.14 0.901 0.422
问:如何在通过“Opening_test”比较平均值的条件下进行方差分析,其中包含“现在关注图像”和“现在关注声音”。
问:我也想通过事后测试来跟进。
这是我尝试过的,但显然不是正确的方法!
# Compute one-way ANOVA test
res.aov <- aov(m ~ stim_ending_t, data = clean_test_master2)
summary(res.aov)
Df Sum Sq Mean Sq F value Pr(>F)
stim_ending_t 1 7.589 7.589 418.8 <2e-16 ***
Residuals 34 0.616 0.018
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
我认为 aov 的结果有问题!stim_ending_t 有 6 个因子,因此上表中的自由度 (Df) 应该 = 5 而不是 != 1。
# post hoc test
TukeyHSD(res.aov, conf.level = 0.99)
Here is the message I got
Error in TukeyHSD.aov(res.aov, conf.level = 0.99) :
no factors in the fitted model
In addition: Warning message:
In replications(paste("~", xx), data = mf) :
non-factors ignored: stim_ending_t
注意:参与者在一个会话中完成了实验,从条件-Opening_text 开始,随机完成另一个。