The rank order question increases the power of the measurement scale by including the characteristic of order to the data. Whereas the categorical data associated with most multiple choice items does not permit us to say that one item is greater than another, rank order data allows for the analysis of differences.

Rank order data uses an answer format that requires the respondent to assign a rank position for the first, second,... up to the nth item to be ordered. This format of assigning position numbers is very versatile. Respondents may be asked to rank a specified subset from the list (such as their first, second, and third choices from a list), or to rank all items in the list. Typical questions might include identifying preference rankings, attribute association strength, first to last, oldest to youngest, or relative position (most , next most, and so forth, until either a set number of items is ordered or all items may be ordered).

Variations: Some variations of the question exist.

Randomize: We know that in elections, being the first on the list increases chances of election. Similar bias occurs in all questionnaires when the same answer appears at the top of the list for each respondent. Randomization corrects this bias by presenting a random choice order for each respondent.

Ties: If ties are permitted, several items may be evaluated as having the same rank. In general this is not a good idea because it weakens the data. However, if ties truly exist, then the ranking should reflect this. If branching is selected and a tie occurs, the first item with a tie is selected. This is an arbitrary rule, but one that makes sense if answers are randomized.

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