A Versatile tool? Applying the Cross-national Error Source Typology (CNEST) to triangulated pre-test data

Rory Fitzgerald, Lizzy Winstone, and Yvette Prestage

Nº 2014-02

DOI :

10.24440/FWP-2014-00002

How to cite this article :

Fitzgerald, R., Winstone, L., & Prestage, Y. (2014). A Versatile tool? Applying the Cross-national Error Source Typology (CNEST) to triangulated pre-test data. FORS Working Paper Series, paper 2014-2. Lausanne: FORS.

Abstract :

There are certain error sources that are unique to cross-national questionnaires, or occur less frequently in single nation studies. Tools that help to identify these errors and separate them bfrom measurement errors that only occur in single nation studies assist the cross-national survey researcher in producing a higher quality source questionnaire. In turn, this supports translators in producing functionally equivalent translations that work well in the target languages and cultures. The Cross-national Error Source Typology (CNEST) was developed as a tool for improving the effectiveness of cross-national questionnaire design and has already proved useful when applied to cognitive interview data. This paper assesses the consistency and versatility of the tool by applying it to triangulated cross-national pre-test data collected in Russia and the UK as part of the development of questions for the European Social Survey (ESS). The benefits and challenges of triangulating pre-test data in a crossnational setting are also highlighted and discussed.

Copyright:

© the authors 2018. This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0) Creative Commons License