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

[Lisa Snel]

Dear Bert,

Thank you for the tip, I am going to try it there!

Best,
Lisa
________________________________
Van: Bert Gunter <bgunter.4567 using gmail.com>
Verzonden: vrijdag 4 januari 2019 17:09
Aan: Lisa Snel
CC: Ista Zahn; r-help using r-project.org
Onderwerp: Re: [R] How to perform Mixed Design ANOVA on MICE imputed dataset in R?

You might wish to post on the r-sig-mixed-models list, which is specifically devoted to mixed effects models, instead of here. You are more likely to find both interest and expertise there.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Fri, Jan 4, 2019 at 7:49 AM Lisa Snel <lisa_1995_s using hotmail.com<mailto:lisa_1995_s using hotmail.com>> wrote:
Dear Ista,

Thank you for your response and the link you have sent me. However, I know the basic things of the MICE package (how impute, to pool and to do basic analyses), but the problem is that I cannot find anything about this specific analysis.

Best,
Lisa
________________________________
Van: Ista Zahn <istazahn using gmail.com<mailto:istazahn using gmail.com>>
Verzonden: vrijdag 4 januari 2019 15:11
Aan: Lisa Snel
CC: r-help using r-project.org<mailto:r-help using r-project.org>
Onderwerp: Re: [R] 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 <lisa_1995_s using hotmail.com<mailto:lisa_1995_s using hotmail.com>> 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
>
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>
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______________________________________________
R-help using r-project.org<mailto:R-help using r-project.org> 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.

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