In this article, you will learn about Paired Comparison Scaling.
Using the Paired Comparison Scaling, the respondent is shown two objects side by side and asked to choose one of them based on a predetermined criteria. Consequently, the results are ordinal.
For physical products, paired comparison scaling is frequently used. There are two ways to analyse the comparison data. In the first place, a researcher can calculate the percentage of respondents who prefer one object over another by combining the matrices for each respondent, dividing the sum by the number of respondents, and multiplying it by 100. All the stimuli can be evaluated simultaneously using this method.
It is also possible to rank paired comparison data using the assumption of transitivity (which states that if brand X is preferred to Brand Y, and Y to Z, then brand X is preferred to brand Z). The researcher adds up all of the matrices to find the order in which the objects are preferred.
Because it necessitates a direct comparison of two items, the paired comparison method works best with small datasets. It also becomes difficult to compare when there are a large number of stimuli available. In addition, if the assumption of transitivity is violated, the results may be skewed by the order in which the objects are placed.