Scaling Sensitive Factorial Survey Analysis

Abstract

In recent decades, factorial survey experiments (FSEs) have become increasingly widespread and successful for analyzing attitudes and behavioral intentions. FSEs measure the ratings of multidimensional treatments embedded in textual scenarios, which are called vignettes. Analyses of FSEs often assume that these ratings are interval scaled. Past research indicates that this assumption is problematic. Therefore, the following article develops a design for interval scaling tests in FSEs and a method for analyzing FSEs which is sensitive to the scaling level of ratings. An exemplary application of scaling sensitive factorial survey analysis in comparison to standard methods yields effect sizes, which are about a sixth larger with regard to the treatments used in the FSE and about a third larger with respect to influences of between respondent differences. The new method also enables the evaluation of interval in contrast to noninterval scaled rating behavior.