How to handle missing data

[thomas123]

Dear all, I have a set of data containing N/A data. Is it possible to use regression model to find out or estimate the missing value?

[Leon]

Imputing missing values is non-trivial, here is a number of google hits on the issue, try one or more and then return here with any questions you may have

[mara]

I included some resources in an similar thread here:

Data prediction for missing data

I'm a big fan of this article on Missing Data Imputation (by Andrew Gelman, I believe) which includes R code for various methods, as well: http://www.stat.columbia.edu/~gelman/arm/missing.pdf Packages worth checking out (mentioned in this RViews post by Joseph Rickert, Missing Values, Data Science and R) Amelia implements the Amelia II algorithm which assumes that the complete data set (missing and observed data) are multivariate normal. Imputations are done via the EMB (expectation-maximization with bootstrapping) algorithm. The JSS paper describes a strategy for combining the models resulting from each imputed data set. The Amelia vignette contains examples. BaBoon provides two varian…

[Leon]

But... Please please remember, that when you're imputing missing data, you are enforcing existing structure in data, which can lead to misconclusions, e.g. with unsupervised clustering

[thomas123]

Bro that's my next step, I would like to compare the structure before and after imputing missing data, including clustering. However I can't upload my dataset here, would like to seek any advice.