我对使用MICE多次插补后在R中执行混合设计方差分析有疑问。我的数据如下：
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,88,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,65,64,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,83,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
因此：我们对舒张压进行了6次重复测量（测量1至6）。分组因子是性别，称为分组。如果是男性，则此变量编码为1；如果是女性，则编码为0。在进行多次插补之前，我们在R中使用了以下代码：
library(reshape)
library(reshape2)
datLong <- melt(dat, id = c("id", "group"), measured = c("measure_1", "measure_2", "measure_3", "measure_4", "measure_5", "measure_6"))
datLong
colnames(datLong) <- c("ID", "Gender", "Time", "Score")
datLong
table(datLong$Time)
datLong$ID <- as.factor(datLong$ID)
library(ez)
model_mixed <- ezANOVA(data = datLong,
dv = Value,
wid = ID,
within = Time,
between = Gender,
detailed = TRUE,
type = 3,
return_aov = TRUE)
model_mixed
这很好。但是，我们的数据不完整。我们缺少使用MICE估算的值：
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,NA,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,NA,NA,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,NA,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
imp_anova <- mice(dat, maxit = 0)
meth <- imp_anova$method
pred <- imp_anova$predictorMatrix
imp_anova <- mice(dat, method = meth, predictorMatrix = pred, seed = 2018, maxit = 10, m = 5)
（归因于虚假数据和简单的归因代码（例如id用作预测变量），归因给出了记录的事件。对于我的真实数据，归因是正确且有效的）
现在，我获得了估算的“ mids”类数据集。我已经在互联网上进行搜索，但是无法找到如何在此估算集上执行混合设计ANOVA的方法，就像我之前使用ezANOVA使用完整集一样。有谁可以并且想要帮助我？