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Case 1 best-worst scaling (also known as MaxDiff) designs involve presenting respondents with a number of items and asking them to pick which is “best” and “worst” of the set. More generally, the respondent is asked which items have the most and least of any given feature (importance, attractiveness, interest, and so on). Respondents complete many sets of items in a row, and from this we can learn how the items rate and rank against one another. One of the reasons I like them as a prejudice researcher is that it can help hide the purpose of the measurement tool: If I ask about 13 different items over 13 different trials, but the one about prejudice only comes up in 4 of the 13 trials, it masks what the questionnaire is actually about. But the most standard use cases involve marketing.

There is a lot of literature out there on how to calculate rating scores for items in these designs across the entire sample (aggregate scores) and within a respondent (individual scores). With a focus on the individual-level measurement, I put together a package called bwsTools that provides functions for creating these designs and analyzing them at both the aggregate and individual level. The package is on CRAN and can be installed by install.packages(“bwsTools”).

Some resources to get you started using the package: