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

Abstract

Split-ballot data are often used to study double standards. The key problem of this design is that individual double standards cannot be identified. We propose a simple two-step approach based on a matching pre-processing of the data to estimate individual double standards. Once this preliminary first step is completed, any statistical technique (e.g., regression models) can be applied on the new data. We illustrate the method with an application concerning gender double standards on attitudes toward age at leaving home using data from the third round of the European Social Survey. We show that the proposed method simplifies regression analyses of the effects of covariates on double standards and offers new opportunities for research on double standards.