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SPSS Topics Discussion > Imputation of categorical missing values in SPSS

Hello all,

I want to know a very basic thing about adjustment of missing values for categorical variables in SPSS. I have a data set containing some categorical variables. Some variables have only two categories 0 and 1. Some variables have 5 categories 0 to 4. Some variables have even 11 categories 0-10. Almost all the variables have missing values. I have 3 questions:

1) How do I impute those missing values in SPSS? Please write the procedure for me that I can understand what steps I need to follow to impute those categorical missing values.

2) I have read about hot-deck imputation while I was searching over net. Is it good for my case (note that I have some continuous variables too in my data set. I read that the background variables need to be categorical.) Again is hot-deck imputation plausible for imputing the missing values of a variable having only two categories (0 and 1)? If hot-deck in applicable is my case, how do I do this in SPSS?

3) How do I impute missing values for the continuous variables? Again if you kindly mention the steps, it will be a great help.

July 21, 2012 | Unregistered CommenterBlain Waan

Hi Blaine,

The SPSS add-on for missing values allows users to conduct multiple imputation models that contain a mix of categorical and continuing variables. This is probably the most user-friendly option available. Unfortunately, conducting a good imputation model is too complex a procedure to appropriately stepped through any form post. However, the SPSS health documentation is usually pretty helpful and provides good examples (if you purchase the add-on for the program to allow you to do the analysis).Unfortunately, it isn't realistic to detail each step of the process in a form post.

With that said, I much prefer to use R to do imputation, and the "MI" package specifically. The author of the package does a good job documenting how to use the package and conduct the procedure, Including examples. Below is a link to the package on the Cran – R – project website, for more information about that. I hope this helps!

http://cran.r-project.org/package=mi

July 28, 2012 | Registered CommenterJeremy Taylor