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Web Survey Bibliography

Title Determinants of Item Nonresponse in the German Internet Panel
Year 2017
Access date 13.04.2017


Relevance & Research Question

Accurate collection and processing of survey data plays an important role in today's data-driven society. The prevention and treatment of measurement error that may occur during these processes have so far been in the focus of several survey methodologists. Item nonresponse (INR) as one source of nonobservation error occurs if participants of a survey leave selected questions unanswered and should not be neglected as it might reduce overall data quality. In my bachelor thesis, I investigated the impact of respondent characteristics and question types - complex, sensitive and neutral ones - on the occurrence of INR using data of the German Internet Panel. Furthermore, applying a multi-level logistic regression, I examined potential interaction effects between both, sociodemographic characteristics and question types. As in online surveys respondents do not face any presence of an interviewer, their overall response behavior might somehow deviate compared to rather traditional sorts of interviews (e.g. CATI, CAPI or PAPI). In particular, older participants might be less familiar with the internet which may be reflected in the answers they provide. The profound analysis of nonsubstantive responses patterns may contribute to a better understanding of its underlying mechanisms and thus help preventing future INR in online surveys.

Methods & Data

In order to investigate the impact of question types, all questions of the questionnaire were evaluated with regard to potential complexity or sensitivity. Therefore, a coding scheme was created, examining each single question of the questionnaire. To detect correlates of INR, two multivariate regression models were developed. The first one included the isolated impact of sociodemographic characteristics and question types on INR, whereas in the second model potential interaction effects were taken into account. Due to the nested data structure, where responses are nested within respondents, a multi-level analysis was applied. As the outcome variable of interest was considered dichotomous, logistic regression was used.

The data were taken from wave 16 of the German Internet Panel. In general, the survey contains questions concerning economic and political attitudes and is obtained via online, self-administered questionnaires.


The findings provide some interesting insights into the patterns of nonsubstantive response behavior. Most independent variables showed to have a significant effect, with complex questions having the highest chance to produce INR. In terms of interaction effects, it could be found that people of lower cognitive abilities happen to struggle more with complex questions than people of higher abilities. In this context, also a gender gap could be proven. With regard to sensitive questions, there exists a weak but still significant connection to rising age.

Conclusion & Added Value

The findings suggest, that on the one hand, item nonresponse is mainly a function of specific respondent characteristics such as cognitive abilities and gender, respectively question characteristics. On the other hand, cross-level interactions between both, respondent and question characteristics, seem to play a crucial role. These results have important implications in terms of the overall questionnaire design, especially order and content of questions. As the application of any subsequent processing is still costly and time-consuming, potential error sources should always be prevented in advance. With my research on item nonresponse, I seek to contribute to the sustainable improvement of data collection through surveys and thus to enable a solid base for further empirical social research.


Year of publication2017
Bibliographic typeConferences, workshops, tutorials, presentations

Web survey bibliography (8390)