Web Survey Bibliography

Title Does the Collection of Ego-Centered Network Data on the Web reduce the Data Quality? An Experimental Comparison of online versus offline Data Collection
Author Matzat, U., Snijders, C.
Source General Online Research Conference (GOR) 2006
Year 2006
Access date 21.09.2006
Abstract We analyze whether differences in kind and quality of ego-centered network data that were collected on the web compared to data collected with the help of an interviewer are caused by the different data collection procedures. The quality of web survey data has been analyzed (Couper 2000) for more or less standard questions. The collection of ego-centered network data, however, is notoriously more difficult than the collection of other survey data because it faces the respondent with a more complex answering task. Until now, we know that the wording of the items influences the measured size of the network and the drop out rate (Lozar Manfreda, Vehovar & Hlebec 2004). Also, it is known that when respondents can freely choose between a web survey and an interview, then those who choose the web survey have a higher drop out rate and more missing values (Snijders & Matzat 2005). However, we do not know whether the web survey itself reduces the data quality or whether the reduction can be explained by other unobserved differences between the groups. In our study university researchers of different disciplines at a Dutch university (n=270) were randomly divided into two groups. They either filled out ego-centered data through a web questionnaire or were probed about their network in a personalized interview. Ego-centered network data collection makes use of so-called \"name generators\" that are both hard to explain properly and moreover give the respondent a special opportunity to shorten the answer procedure. For this reason, interviewers are often deemed critical in the proper collection of ego-centered network data. Our analysis provides a strong test of whether the collection of network data through the Internet reduces the data quality. One could argue that respondents who are not interviewed in person are tempted to answer in a much more time saving manner than other respondents, and are moreover more likely to make mistakes or simply quit. We focus on drop out rates, the number of missing values, the size and density of the ego-centered networks, as well as other properties of the networks. The paper presents the results of the hypotheses testing.
Access/Direct link Conference homepage (abstract)
Year of publication2006
Bibliographic typeConferences, workshops, tutorials, presentations
Full text availabilityNon-existant
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Web Survey Bibliography - General Online Research Conference (GOR) 2006 (29)