Question

目标：根据重复测量ANOVA计算eta值的95％置信区间。

设计是双因素设计（因子1有3个等级，因子2有7个等级），与30个受试者完全交叉。但是，我不确定我是否正确地进行自举以计算eta的置信区间。我使用boot（）函数按主题引导样本，但仅将因子和级别留在因子中。所以我不确定我是否正确这样做 - 我是否需要进行更复杂的自举/重采样，我按照因子/等级进行重新采样，或者只是在主题级别进行。我的代码似乎给出了合理的结果......

library(ez)
library(boot)
library(reshape2)

###create a data.frame for a 2-factor (Factor1-3 levels, Factor2-7 levels) fully crossed design with 30 subjects & fill fake data values
subject.number<-factor(rep(1:30,each=21))
factor1.levels<-rep(rep(c("level1","level2","level3"),each=7),30)
factor2.levels<-rep(rep(c("level1","level2","level3","level4","level5","level6","level7"),3),30)
set.seed(1234)
fake.data<-rnorm(630,mean=3)
dframe<-data.frame(subject.number,factor1.levels,factor2.levels,fake.data)
names(dframe)<-c("Subject","Factor1","Factor2","OutcomeValue")


###to work with boot() convert from long to wide format
dframe.wide<-dcast(dframe,Subject~Factor1+Factor2,value.var="OutcomeValue")


###function to use with boot() to calculate generalized eta value for Factor1, Factor2, and Factor1xFactor2 interaction in a repeated measures ANOVA

generalized_eta<-function(data,indices){
  d.wide<-data[indices,] #use boot() indices to sample data

  #now that have used indices from boot(), convert data back to long with correct Factor labeling
  dframe.long<-melt(d.wide,value.name="OutcomeValue",id="Subject")
  dframe.long<-cbind(dframe.long,colsplit(dframe.long$variable,"_",c("Factor1","Factor2")))
  dframe.long$Factor1<-factor(dframe.long$Factor1)
  dframe.long$Factor2<-factor(dframe.long$Factor2)
  dframe.long$Subject<-factor(dframe.long$Subject)

  #do repeated measures ANOVA with ezANOVA() which calculates generalized eta
  aov.ez = ezANOVA(data = dframe.long, dv = .(OutcomeValue), wid = .(Subject), within = .(Factor1,Factor2), type = 1)
  #return the three generalized eta values - Factor1, Factor2, Factor1xFactor2
  return(aov.ez[[1]]$ges)
}


###call boot() to do the bootstrap - only 200 to make it fast
results<-boot(data=dframe.wide,statistic=generalized_eta,R=200)


###plot the bootstrap results
plot(results,index=1) #for Factor1
plot(results,index=2) #for Factor2
plot(results,index=3) #for Factor1xFactor2

###create 95%-CI from bootstrap results
boot.ci(results,type="bca",index=1) #for Factor1
boot.ci(results,type="bca",index=2) #for Factor2
boot.ci(results,type="bca",index=3) #for Factor3

R：不清楚如何为重复测量ANOVA引导eta值

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