In this research project we will demonstrate the vulnerability of several statistical tests and procedures towards response sets. Using data sets from two standardized surveys (face to face & web), secondary data analyses were conducted. Given the importance of the mode of data collection, as it can alleviate or exacerbate response sets, we used data gathered in face-to-face interviews as well as via mail and online surveys. As expected, we found that the overall number of response sets was low, with the highest number found in the online survey. Further testing showed, however, that despite their low number response sets are far from negligible: whilst simple bivariate tests such as cross tabulations and means response sets are hardly affected due to the low share of invalid answers results of multivariate procedures are considerably altered. Our results show that a share of 0.001 percent (or 24 of 19.800 respondents) of respondents using response sets change the results of cluster analyses (k-means) significantly. Based on these findings, we finally discuss how to identify and deal with respondents who used response sets.