I have a survey data with categorical outcome variable (yes, no, don't know) which reflects the acceptance of some situation by respondents. My concern is how to deal with Don't know answers, I really doubt I should drop these observations, because:
- it shrinks my dataset from around 14400 to around 13000, which is considerable;
- I have intuition that DK answer carry some info and thus not random.
So my questions are:
- One suggested that non-randomness influences the estimated probability and I should check for it, but how do we check for randomness in Stata?
- If keeping DK answers is desired then multiple imputation (for example) is the way to deal with this issue. Is there any source/links that I could use to make myself familiar with what multiple imputation is and how it is done in Stata?
- Almost all papers I read on my topic use logistic regression, I wonder what is the justification behind it. Is there any links/source that compare different probabilistic approaches for not-binary outcome variable (in my case it will be three-asnwers categorical outcome variable) and how we choose between them?