Evaluating the quality of survey and administrative data with generalized multitrait-multimethod models

Administrative data are increasingly important in statistics, but, like other types of data, may contain measurement errors. To prevent such errors from invalidating analyses of scientific interest, it is therefore essential to estimate the extent of measurement errors in administrative data. Currently, however, most approaches to evaluate such errors involve either prohibitively expensive audits or comparison with a survey that is assumed perfect. We introduce the “generalized multitrait-multimethod” (GMTMM) model, which can be seen as a general framework for evaluating the quality of admin∗The authors are indebted to Hal Stern and Jörg Drechsler for their comments as well as Barbara Felderer for her assistance in preparing the data. This work was supported by the Netherlands Organization for Scientific Research (NWO) [Veni grant number 451-14-017].