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How to perform Mixed Design ANOVA on MICE imputed data in R?
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I have a question about performing a Mixed Design ANOVA in R after multiple imputation using MICE. My data is as follows:
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)
So: we have 6 repeated measurements of diastolic blood pressure (measure 1 till 6). The grouping factor is gender, which is called group. This variable is coded 1 if male and 0 if female. Before multiple imputation, we have used the following code in R:
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$ID)
library(ez)
model_mixed <- ezANOVA(data = datLong,
dv = Value,
wid = ID,
within = Time,
between = Gender,
detailed = TRUE,
type = 3,
return_aov = TRUE)
model_mixed
This worked perfectly. However, our data is not complete. We have missing values, that we impute using MICE:
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,NA,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,NA,NA,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,NA,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
imp_anova <- mice(dat, maxit = 0)
meth <- imp_anova$method
pred <- imp_anova$predictorMatrix
imp_anova <- mice(dat, method = meth, predictorMatrix = pred, seed = 2018, maxit = 10, m = 5)
(The imputation gives logged events, because of the made-up data and the simple imputation code e.g id used as a predictor. For my real data, the imputation was correct and valid)
Now I have the imputed dataset of class ‘mids’. I have searched the internet, but I cannot find how I can perform the mixed design ANOVA on this imputed set, as I did before with the complete set using ezANOVA. Is there anyone who can and wants to help me?
r anova mixed-models
asked Jan 3 at 15:53
Anna_70Anna_70
263
add a comment |
I have a question about performing a Mixed Design ANOVA in R after multiple imputation using MICE. My data is as follows:
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,88,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,65,64,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,83,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
So: we have 6 repeated measurements of diastolic blood pressure (measure 1 till 6). The grouping factor is gender, which is called group. This variable is coded 1 if male and 0 if female. Before multiple imputation, we have used the following code in R:
library(reshape)
library(reshape2)
datLong <- melt(dat, id = c("id", "group"), measured = c("measure_1", "measure_2", "measure_3", "measure_4", "measure_5", "measure_6"))
datLong
colnames(datLong) <- c("ID", "Gender", "Time", "Score")
datLong
table(datLong$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
This worked perfectly. However, our data is not complete. We have missing values, that we impute using MICE:
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)
(The imputation gives logged events, because of the made-up data and the simple imputation code e.g id used as a predictor. For my real data, the imputation was correct and valid)
Now I have the imputed dataset of class ‘mids’. I have searched the internet, but I cannot find how I can perform the mixed design ANOVA on this imputed set, as I did before with the complete set using ezANOVA. Is there anyone who can and wants to help me?
r anova mixed-models
asked Jan 3 at 15:53
Anna_70Anna_70
263
I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11
add a comment |
I have a question about performing a Mixed Design ANOVA in R after multiple imputation using MICE. My data is as follows:
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)
So: we have 6 repeated measurements of diastolic blood pressure (measure 1 till 6). The grouping factor is gender, which is called group. This variable is coded 1 if male and 0 if female. Before multiple imputation, we have used the following code in R:
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$ID)
library(ez)
model_mixed <- ezANOVA(data = datLong,
dv = Value,
wid = ID,
within = Time,
between = Gender,
detailed = TRUE,
type = 3,
return_aov = TRUE)
model_mixed
This worked perfectly. However, our data is not complete. We have missing values, that we impute using MICE:
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,NA,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,NA,NA,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,NA,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
imp_anova <- mice(dat, maxit = 0)
meth <- imp_anova$method
pred <- imp_anova$predictorMatrix
imp_anova <- mice(dat, method = meth, predictorMatrix = pred, seed = 2018, maxit = 10, m = 5)
(The imputation gives logged events, because of the made-up data and the simple imputation code e.g id used as a predictor. For my real data, the imputation was correct and valid)
Now I have the imputed dataset of class ‘mids’. I have searched the internet, but I cannot find how I can perform the mixed design ANOVA on this imputed set, as I did before with the complete set using ezANOVA. Is there anyone who can and wants to help me?
r anova mixed-models
asked Jan 3 at 15:53
Anna_70Anna_70
263
I have a question about performing a Mixed Design ANOVA in R after multiple imputation using MICE. My data is as follows:
id <- c(1,2,3,4,5,6,7,8,9,10)
group <- c(0,1,1,0,0,1,0,0,0,1)
measure_1 <- c(60,80,90,54,60,61,77,67,88,90)
measure_2 <- c(55,88,88,55,70,62,78,66,65,92)
measure_3 <- c(58,88,85,56,68,62,89,62,70,99)
measure_4 <- c(64,80,78,92,65,64,87,65,67,96)
measure_5 <- c(64,85,80,65,74,69,90,65,70,99)
measure_6 <- c(70,83,80,55,73,64,91,65,91,89)
dat <- data.frame(id, group, measure_1, measure_2, measure_3, measure_4, measure_5, measure_6)
dat$group <- as.factor(dat$group)
So: we have 6 repeated measurements of diastolic blood pressure (measure 1 till 6). The grouping factor is gender, which is called group. This variable is coded 1 if male and 0 if female. Before multiple imputation, we have used the following code in R:
library(reshape)
library(reshape2)
datLong <- melt(dat, id = c("id", "group"), measured = c("measure_1", "measure_2", "measure_3", "measure_4", "measure_5", "measure_6"))
datLong
colnames(datLong) <- c("ID", "Gender", "Time", "Score")
datLong
table(datLong$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
This worked perfectly. However, our data is not complete. We have missing values, that we impute using MICE:
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)
(The imputation gives logged events, because of the made-up data and the simple imputation code e.g id used as a predictor. For my real data, the imputation was correct and valid)
Now I have the imputed dataset of class ‘mids’. I have searched the internet, but I cannot find how I can perform the mixed design ANOVA on this imputed set, as I did before with the complete set using ezANOVA. Is there anyone who can and wants to help me?
r anova mixed-models
r anova mixed-models
asked Jan 3 at 15:53
Anna_70Anna_70
263
asked Jan 3 at 15:53
Anna_70Anna_70
263
asked Jan 3 at 15:53
Anna_70Anna_70
263
asked Jan 3 at 15:53
Anna_70Anna_70
263
asked Jan 3 at 15:53
Anna_70Anna_70
263
263
I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11
add a comment |
I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11
I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11
I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11
add a comment |
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I think cross validated would be a better forum for your question.
– Mankind_008
Jan 3 at 16:11