I am carrying out a logistic regression analysis in entrepreneurship research, in which one of the main independent variables, "innovativeness", is a company trait based on two different questions ("product's/service's potential to change the market" and "product/service novelty"). As these two were internally consistent with a high Cronbachs alpha score, it was decided to create one variable with a
9 point Likert scale instead of the
5 point scale of the individual variables. The final value is the two respective values added together and divided by two
The problem is that there is a range of missing values for one or the other variable (
32), meaning that the entrepreneur "didn't know" or just didn't answer the question. This is unfortunate as the complete sample (
182) is not very big in the first place.
Is it legitimate to take one of the values, if the other is missing, and use it as a proxy for the underlying construct (innovativeness)? Or would this create a bias greater than the missing values might potentially lead to?