Hi,
I might write a little function that does different things depending
on the class of the variable. Along the lines of:
where i is a column index:
function(i) {
if (is.numeric(imputeddata[, i])) {
something
} else if (is.factor(imputeddata[, i])) {
something else
} etc.
then you can just do:
combined <- lapply(1:nrow(imputeddata), yourfun)
Alternately, you could consider some single imputation approaches
since that is what you essentially end up doing.
Cheers,
Josh
On Thu, Jan 12, 2012 at 10:16 PM, Felipe Nunes <felipnu...@gmail.com> wrote:
> Hi all,
>
> after using Amelia II to create 10 imputed data sets I need to average them
> to have one unique data that includes the average for each cell of the
> variables imputed, in addition to the values for the variables not imputed.
> Such data has many variables (some numeric, other factors), and more than
> 20000 observations. I do not know how to average them out. Any help?
>
> Below I provide a small example:
>
> Suppose Amelia provided two datasets:
>
> d1 <- data.frame(subject = c("Felipe", "John"), eat1 = 1:2, eat3 = 5:6, trt
> = c("t1", "t2"))
>
> d2 <- data.frame(subject = c("Felipe", "John"), eat1 = 3:4, eat3 = 6:7, trt
> = c("t1", "t2"))
>
> I tried
>
> (d1 + d2)/2
>
> but I lose my factors. mean() did not work either.
>
> The result I'd like is:
>
> subject eat1 eat3 trt
> 1 Felipe 2 5.5 t1
> 2 John 3 6.5 t2
>
> thanks,
>
> *Felipe Nunes*
> CAPES/Fulbright Fellow
> PhD Student Political Science - UCLA
> Web: felipenunes.bol.ucla.edu
>
> [[alternative HTML version deleted]]
>
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--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
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