The Advanced MaxDiff Aggregate test is a great way to compare many alternatives without overwhelming respondents by asking them to read and consider all items at once. It takes a list of your items to be compared and shows them in a balanced order to each respondent several items at a time.

How It Works

The method focuses on collecting general aggregate information without the intention to obtain individual-level estimates. In typical settings, respondents would see 3–5 screens.

In deciding which items to show on the next screen of the MaxDiff, the system focuses on ensuring equal coverage of pairs of items among all respondents. Items are chosen randomly, with bias toward pairs of items that were seen less frequently overall across respondents.

The core analysis of respondents' preferences is performed by the Maximum Likelihood Multinomial Logit model.

The Statistics Page

The statistics page has three display modes:

1. Preference Likelihood (X/screen) — represents the likelihood that an item would be preferred over (X−1) other randomly selected items in the set. This score is appropriate when the MaxDiff exercise shows X items per exposure.
2. Utility Scores — the raw regression coefficients estimated at the aggregate level. They are zero-centered so that 0 represents average performance. The more positive an item's utility, the more it is preferred; the more negative, the less it is preferred.
3. Average-based PL (50% baseline) — represents the Preference Likelihood that an item would be preferred over one other randomly selected item. A score above 50% indicates a better-than-average performer.

When applying filters to a survey, Advanced MaxDiff Aggregate questions will show aggregate statistics for the current subset of respondents.

Export includes:

• Raw data export — data on what each respondent saw and what decision was made on each task.