A model for transferring variables between different data-sets based on imputation of individual scores

It is an often-encountered problem that variables of interest are scattered in different datasets. Given the two methodologically similar surveys, a question not asked in one survey could be seen as a special case of missing-data problem (Gelman et al., 1998). The paper presents a model for transferring variables between different datasets, applying the procedures for multiple imputation of missing values. The feasibility of this approach was assessed using two Dutch surveys: Social and Cultural Developments in The Netherlands (SOCON 2000) and the Dutch Election Study (NKO 2002). An imputation model for the left–right ideological self-placement was developed based on the SOCON survey. In the next step, left–right scores were imputed to the respondents from the NKO study. The outcome of the imputation was evaluated, first, by comparing the imputed variables with the left–right scores collected in three waves of the NKO study. Second, the imputed and the original NKO left–right variables are compared in terms of their associations with a broad set of attitudinal variables from the NKO dataset. The results show that one would reach similar conclusions when using the original or imputed variable, albeit with the increased risk of making Type II errors.