We have all seen them when reviewing survey data: respondents where something does not look right, but there is not enough evidence to remove them. I will test whether deeper patterns within a respondent's answers and similarities between respondents can uncover low-quality responses that standard checks miss. Across multiple studies, I will examine which checks add useful evidence, approaches to calibrating respondent similarity, and whether removing flagged respondents materially changes the research results.
