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Response quality and ideological dispositions: an integrative approach using geometric and classifying techniques

Abstract

When analyzing survey data, response quality has consequential implications for substantial conclusions. Differences in response quality are usually explained by personality, or socio-demographic or cognitive characteristics. Little, however, is known about how respondents’ political attitudes, values, and opinions impact on quality aspects. This is a striking analytical omission, as potential associations between political values and various forms of response biases and artefacts call into question surveys’ ability to represent ‘public opinion’. In this contribution, response quality is traced back to respondents’ political and ideological dispositions. For this purpose, a relational understanding of response quality is applied that takes into account different aspects of response behaviors, as well as the interrelations between these indicators. Using data from the US General Social Survey (2010–2014), an empirical typology of response quality is created via finite mixture analysis. The resulting classes are then related to positions in the US field of ideological dispositions, constructed via multiple correspondence analysis. The analyses reveal that there are (1) different combinations of response patterns and thus different empirical response types, and (2) that these types of response quality systematically vary with regard to the respondents’ political and ideological (dis)positions. Implications of the findings for public opinion surveys are discussed.

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Fig. 1
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Notes

  1. E.g., the request to select a certain answer category as proof that instructions were read (Revilla 2016; Meade and Craig 2012).

  2. Due to coding inconsistencies and the small number of cases with missing values in some variables, ‘don’t know’ and ‘no answer’ are treated as a single category in the analysis.

  3. Applying MCA to data from one ballot only yields a similar spatial structure to the one reported in our results.Regarding future analyses, the recent development of Specific MCA constitutes a promising and adequate alternative to the procedure chosen here.

  4. Cross signifies above average contribution to horizontal axis; filled dot signifies above average contribution to vertical axis; empty dot signifies above average contribution to both axes.

  5. Categories comprising less than one percent of the sample are not displayed. The response style classes ‘middle’ and ‘middle 7pt,’ as well as middle age groups, are located very close to the centroid and thus not displayed for reasons of clarity.

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Barth, A., Schmitz, A. Response quality and ideological dispositions: an integrative approach using geometric and classifying techniques. Qual Quant 52, 175–194 (2018). https://doi.org/10.1007/s11135-016-0458-3

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Keywords

  • Data quality
  • Response quality
  • Correspondence analysis
  • Finite mixture modeling