mixed-mode designs: cognitive equivalence

Instead of separating out mode effects from nonresponse and noncoverage effects through statistical modeling, it is perhaps better to design our mixed-mode surveys in such a way so that mode effects do not occur. The key principle in preventing the mode effects from occurring, is to make sure that questionnaires are cognitively equivalent to respondents. This means that no matter in which survey mode the respondents participate, they would give the same answer. In my opinion, there are two ways to achieve this.

1. choose a mix of modes that lead to a cognitively equivalent survey process. The survey process is very different in a questionnaire administered in a telephone vs. an Internet mode. Some mode combinations are can however be combined without great differences between they survey process across the modes:

- combine face-to-face with telephone modes: the mode of communication is in both modes aural with an interviewer asking and recording answers. The only difference is that the interviewer is physically present in the face-to-face survey, and not in the telephone survey.
- combine mail and Internet modes. Differences between these modes are minimal. Whereas in the United States it is difficult to sample addresses (but not impossible), in Europe, this combination can easily be implemented. Don  Dillman talks about some experiments with this method on the 2009 AAPOR conference (thanks to www.pollster.com).

2. The second way is to use nonequivalent survey modes (for example the telephone and internet), but design the individual survey questions in such a way that they are still equivalent across modes. This implies that all questions should be simple, short and clear, and that there should be as few answer categories as possible (i.e. yes/no and similar). This means that it would be difficult to ask for attitudes or opinions in such a mixed mode design.

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Peter Lugtig
Associate Professor of Survey Methodology

I am an associate professor at Utrecht University, department of Methodology and Statistics.

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