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Interviewers’ Deviations in Surveys

Impact, Reasons, Detection and Prevention


Edited By Peter Winker, Natalja Menold and Rolf Porst

Survey data are used in many disciplines including Social Sciences, Economics and Psychology. Interviewers’ behaviour might affect the quality of such data. This book presents the results of new research on interviewers’ motivation and behaviour. A substantial number of contributions address deviant behaviour, methods for assessing the impact of such behaviour on data quality and tools for detecting faked interviews. Further chapters discuss methods for preventing undesirable interviewer effects. Apart from specific methodological contributions, the chapters of the book also provide a unique collection of examples of deviant behaviour and its detection – a topic not overly present in literature despite its substantial prevalence in survey field work. The volume includes 13 peer reviewed papers presented at an international workshop in Rauischholzhausen in October 2011.


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III Discourses on Interviewers Behavior and Deviations in Survey Data


Interviewer Behavior and the Quality of Social Network Data1 Josef Brüderl, Bernadette Huyer-May, Claudia Schmiedeberg Abstract Interviewer effects are a typical – although often neglected – phenomenon of social network data collected in personal interviews. We analyze the ego-centered network data provided by the German Family Panel and find large interviewer effects which cannot be explained by interviewer or respondent characteristics. These interviewer effects are caused to a large degree by two groups of interviewers, i.e. those who elicit less network persons than the average (“fraudulent” interviewers) and those who generate particularly large networks (“diligent” interviewers). We suggest a method to identify these groups of interviewers. Introduction In recent years, social network analysis has gained popularity (for an overview see e.g. Wassermann and Faust 2009). The majority of social network studies have relied on data gathered by standardized personal interviews (Marsden 1990, Matzat and Snijders 2010). But caution is advised as social network data are vulnerable to “noise” (Fischer 2009) as well as to interviewer and design ef- fects. These effects may result from deviating interviewer behavior. In contrast to faked interviews, which most of the other chapters of this volume (e.g. Bredl et al. 2013, Menold et al. 2013) deal with, in our case the interviewers’ devia- tions are limited to a small part of the interview whereas other parts of the data should not be affected. Nevertheless, according to AAPOR (2003) this can be seen as a (partial) falsification of interviews. In the research tradition on falsifi- cations generated...

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