I'm currently trying to figure out how to impute missing values in my panel data. I'm using the mice
package in R and the following code:
miceIMP <- mice(dat, m = 10, maxit = 5, print=FALSE)
miceOutput <- complete(miceIMP)
My data is panel data which has missing values in a numeric data column (-> Deal Value). The other columns are factor variables with 17 levels (year), 38 levels (countries) and 19 levels (industries). The data has approx. 16,000 lines, hence, it's a larger data set. I already tried to reduce maxit and m to 1, but that didn't seem to change anything. I also changed the imputation methods, but with e.g. "norm" the imputed values become negative -> this is my second problem, negative values don't make sense. Here is a screenshot of my data. Data Example
So my questions is:
- Can you tell me how I'm reducing the running time (significantly) and simultaneously ensure that the imputed values will not become negative?
Thank you for your help.