607
Methods for Maximizing Comparability in Cross-National and Cross-Cultural Surveys

Thursday, 19 July 2018: 10:30-12:20
Location: 203D (MTCC NORTH BUILDING)
RC33 Logic and Methodology in Sociology (host committee)

Language: English

Cross-national and cross-cultural research is an absolute necessity to understand contemporary human societies. To be useful comparative survey research needs to meet high scientific standards of reliability and validity and achieve functional equivalence across surveys. This is challenging because comparative survey research is a large-scale and complex endeavor that must be well-designed and well-executed to minimize error and maximize equivalence. This goal can be notably advanced by the application of the total survey error paradigm to cross-national/cultural survey research.

                First, this session will cover the concept of total survey error, including interactions between the error components, its application when multiple surveys are involved, and comparison error across cross-national surveys. Second, obtaining functional equivalence and similarity in cross-national surveys will be  addressed. Third, the challenges of doing cross-national surveys will be considered and how combining traditional approaches for maximizing functional equivalence can minimize comparison error and maximize comparative reliability and validity. Fourth, attention will be given to minimizing comparison error in question wordings in general and the availability of on-line resources for developing and testing items to be used in cross-national surveys. Special attention is given to dealing with differences in language, structure, and culture. Fifth, issues relating to evaluating scales designed to measure constructs in comparative survey research will be a topic to be examined.  Finally, the importance of documentation for datasets is a topic on interest.



Session Organizer:
Tom W SMITH, University of Chicago, USA
Oral Presentations
Testing the Universalism of Bourdieu’s Homology Thesis: A Challenge for Comparative Analysis.
Yannick LEMEL, GEMASS, University Paris4-Sorbonne, France; Dominique JOYE, Lausanne University, Switzerland
How to Compare When Data Come from Diverse Sources: A 4-Level Model of Change in Institutional Trust over Time
Claire DURAND, University of Montreal, Canada; Luis Patricio PENA IBARRA, Université de Montréal, Canada; Nadia REZGUI, Université de Montréal, Canada
Measuring Social Networks and Social Resources in Comparative Perspective
Dominique JOYE, Lausanne University, Switzerland; Marlène SAPIN, FORS Lausanne, Switzerland
Using Paradata to Monitor Interviewers’ Instrument Navigation Behavior and Inform Instrument Technical Design: Case Studies from a National Household Surveys in Ghana and Thailand
Yu-Chieh LIN, Survey Research Center, University of Michigan, USA; Gina-Qian CHEUNG, Survey Research Center, University of Michigan, USA; Beth Ellen PENNELL, Survey Research Center, University of Michigan, USA; Kyle KWAISER, Survey Research Center, University of Michigan, USA