I used AmeliaView to create 5 imputed datasets. I want to pool the 5 imputed
datasets into one to get pooled descriptive information (means, SD, min/max,
etc) that is needed to calculate RCI scores (corrected for measurement error
and practice effects).
The formula to calculate RCI is ((X2 - X1) - (M2 - M1))/S.E.D. where
X1 is observed pre-test score
X2 is observed post-test score
M1 is the group mean pre-test score
M2 is the group mean post-test score, and
S.E.D. is the standard deviation of the mean observed difference score.
My data is currently in long form. I have an ID variable, pre/post data, week,
and imputed dataset number.
ID var1 var2 var3 var4 week impdataset#
555 16 10 8.87 6 3 1
555 18 12 9 6 7 1
777 12 10 9 7 3 2
777 15 13 8 6 7 2
I have searched several sites, but none of the threads exactly answer my
question.
For instance:
I was able to bind/append them into one dataset using:
> ameliaimpute <- rbind(imp1, imp2, imp3, imp4, imp5)
I see I can use packages like Zelig to conduct regression on bound data, but I
don't see a way to get the descriptives on pooled data.
I also tried MICE - but it is just appending the imputed datasets also.
>cogspss->read.spss("cogvaronly0806.sav",use.value.labels=TRUE,
>to.data.frame=TRUE)
>imp <-mice(cogspss, maxit=5)
>com <- complete(imp, "long", inc=TRUE)
>com <- cbind(com, Imputation_ = as.integer(com$.imp)-1)
>write.csv(com, "impmicedata.csv")
One person mentions "I know that I can use Rubin's rules (implemented through
any multiple imputation package in R) to pool means and standard errors..."
This sounds like it would answer my question but I have not been able to find a
tool that does this.
RStudio Version 0.98.953
AmeliaView 1.7.2.
R x64 3.0.2
Windows 7 Enterprise 64 bit
Thank you for your time.
K-Rawson
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