I'd like to create a composite item from variables with the following scale: strongly disagree, disagree, neither agree or disagree, agree, strongly agree and don't know.

I was going to code the scale as 1=strongly disagree, 5=strongly agree, and calculate the composite item with these values. However I don't know how I would code 'don't know' answers (which are about 2% of total answers in the overall sample for all variables).

Any suggestions on how to do this or should I just be treating them as missing data and not include them in my composite item?

  • 1
    $\begingroup$ Two ideas: 1) Code them as don't know and then use the average (of nonmissing) rather than the sum 2) If you are using this sum for something else (e.g. as part of a regression) try multiple imputation. $\endgroup$
    – Peter Flom
    Sep 3, 2012 at 17:19

1 Answer 1


There is not really a right answer to this, because you are defining the composite scale. It is what you say it is. The question is what kind of composite scale is relevant to answering the question you are interested in answering.

I suspect that given the very small number of "don't know" responses, you will lose very little information by just coding the "don't know" responses as 3s, which is by far the simplest solution. Then you can move on to worrying about problems that affect more than 2% of your data, which there surely are given that you are looking at survey responses.

The one caveat to this suggestion is if you really can identify some important (for your application) difference between "don't know" and "neither agree nor disagree". Ask yourself the following questions. 1) If you took away the "don't know" option, do you think there is any chance that the respondents who gave that response would have given an answer other than "neither agree nor disagree"? 2) Do you think anyone else's response have changed without the "don't know" option? I am guessing the answer to these questions is going to be no.


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