Matching pre-processing of split-ballot survey data for the analysis of double standards

Split-ballot data are often used to study double standards. The key problem of this design isthat individual double standards cannot be identified. I propose a simple two-step approachbased on a matching pre-processing of the data to estimate individual double standards. Oncethis preliminary first step is completed, any statistical technique (e.g., regression models) canbe applied on the new data. I apply the method to gender double standards on attitudestoward the age one leaves home by using data from the third round of the European SocialSurvey. The proposed method simplifies regression analyses of the effects of covariates on dou-ble standards and offers new opportunities for research on double standards.