Repeated Measures ANOVA (3)

• 今、検出したいのは、個人のばらばらを考慮した上で、groupごとに時間経過での違いがあること(Withinのgroup:time項が有意であること)

> demo3 <- read.csv("http://www.ats.ucla.edu/stat/data/demo3.csv")
> ## Convert variables to factor
> demo3 <- within(demo3, {
+   group <- factor(group)
+   time <- factor(time)
+   id <- factor(id)
+ })
> 
> par(cex = .6)
> 
> with(demo3, interaction.plot(time, group, pulse,
+   ylim = c(10, 60), lty = c(1, 12), lwd = 3,
+   ylab = "mean of pulse", xlab = "time", trace.label = "group"))
> 
> demo3.aov <- aov(pulse ~ group * time + Error(id), data = demo3)
> summary(demo3.aov)

Error: id
          Df Sum Sq Mean Sq F value  Pr(>F)    
group      1 2035.0  2035.0   343.1 1.6e-06 ***
Residuals  6   35.6     5.9                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Error: Within
           Df Sum Sq Mean Sq F value   Pr(>F)    
time        2 2830.3  1415.2   553.8 1.52e-12 ***
group:time  2  200.3   100.2    39.2 5.47e-06 ***
Residuals  12   30.7     2.6                     
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 

> demo4 <- read.csv("http://www.ats.ucla.edu/stat/data/demo4.csv")
> ## Convert variables to factor
> demo4 <- within(demo4, {
+   group <- factor(group)
+   time <- factor(time)
+   id <- factor(id)
+ })
> par(cex = .6)
> 
> with(demo4, interaction.plot(time, group, pulse,
+   ylim = c(10, 60), lty = c(1, 12), lwd = 3,
+   ylab = "mean of pulse", xlab = "time", trace.label = "group"))
> 
> demo4.aov <- aov(pulse ~ group * time + Error(id), data = demo4)
> summary(demo4.aov)

Error: id
          Df Sum Sq Mean Sq F value   Pr(>F)    
group      1 2542.0    2542     629 2.65e-07 ***
Residuals  6   24.3       4                     
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Error: Within
           Df Sum Sq Mean Sq F value   Pr(>F)    
time        2      1     0.5   0.079    0.925    
group:time  2   1736   868.2 137.079 5.44e-09 ***
Residuals  12     76     6.3                     
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1