I have a scenario where i have been given a correlation matrix and in it i have many of the missing data. I would like to seek all of your help to please help me to figure out how could i do my best estimate in predicting those missing values in my correlation matrix.
I also would like to add that the correlation matrix contains non normalized data.
I have read SAS publication and i saw it offers an multiple imputation method for dealing with missing data. My question is :
1) Is IM dealing with only normalized data, but in my case, the matrix contains non normalized data.
2) Is IM only dealing with missing data, but in my case, I don't have a simple case of missing data, I have missing correlation coefficient in a correlation matrix. So could i use IM?
You have a missing value in a correlation matrix. This happens because there is no data for that pair of variables. Which definitely leaves you with a very serious problem -- how do you estimate the correlation when you have no data?
Let me ask you this ... how would you estimate the mean of a variable if you had no data to go on? Same answer applies to correlation.
Message was edited by: Paige