# How to perform Mixed Design ANOVA on MICE imputed dataset in R?

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## How to perform Mixed Design ANOVA on MICE imputed dataset in R?

 Hi all, 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? Best, Lisa         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: How to perform Mixed Design ANOVA on MICE imputed dataset in R?

 Hi Lisa, The package web page at http://stefvanbuuren.github.io/mice/ has all the info you need to get started. Best, Ista On Fri, Jan 4, 2019 at 3:29 AM Lisa Snel <[hidden email]> wrote: > > Hi all, > > 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? > > > Best, > > Lisa > >         [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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