Contents
How do you analyze maximum differential data?
The simplest way to analyze MaxDiff data is to count up how many people selected each alternative as being most preferred. The table below shows the scores. Apple is best. Google is second best.
How do you interpret MaxDiff results?
MaxDiff Analysis Reporting & Results
- The higher the score, the more appealing an attribute is to your audience.
- A positive score means that the attribute was selected as MOST appealing more often than LEAST appealing.
- A negative score means that the attribute was selected as LEAST appealing more often than MOST appealing.
What is MaxDiff in a survey?
MaxDiff (otherwise known as Best-Worst) quite simply involves survey takers indicating the ‘Best’ and the ‘Worst’ options out of a given set. Implemented within an appropriate experimental design we can obtain a relative ranking for each option.
What is rank order data?
Rank order data (also known as ordinal data) is a type of quantitative data. Numerical rankings involves assigning a numerical value in order to some set of stimuli (1st, 2nd, 3rd, etc.). The relative numerical value indicates only an ordering of items and the distance between any two values may not be identical.
What are MaxDiff utility scores?
A utility score is a measure of relative desirability or worth. When computing utility scores using logit, latent class, or HB every item in the MaxDiff project receives a utility (preference score). The higher the utility, the more likely the item is to be chosen as best (and not chosen as worst).
What is a MaxDiff exercise?
Maximum Difference Scaling (MaxDiff) is a survey research technique for obtaining preference scores for a list of items. It allows you to prioritize a set of product features or test concepts. This exercise is carefully designed to enable the researcher to analyze and derive relative preference scores for each item.
What data has the benefit of a true zero point?
Data that have all the features of interval data, with the added benefit of a true zero point.