How should I handle missing values for survey data (missing due to adding a new set of items mid collection)? I designed a survey (mostly Likert scales) and began to collect responses. After collecting several responses I decided to include an additional scale comprised of 9 items. The newly added scale will be an important predictor. My dependent variables are themselves Likert scales. I will do ordinal probit regression.
Collection before adding the new item was ~200, but total sample size is expected to be ~500.
Should my data be considered to be MCAR, MAR, or MNAR? What is the best way to handle such missing data?

If the participant characteristics don't change over time, then assuming MCAR is probably reasonable for this situation. Under that assumption you could exclude any participants without the new scale from the regression analysis and the results would still be valid, although with reduced sample size. Alternatively, you could try multiple imputation to replace the missing measurements for the first 200 participants. That can be a bit dangerous with so much missing data, but if the data is MCAR I think it should be ok. If there are strong relationships between the other scale questions and the missing scale question then I would try multiple imputation, but it's hard to say without knowing the details.
