In the recent decades we have seen major efforts in establishing a European framework of indicators trying to monitor social change and societal developments all over Europe. Those "official statistics" are often generated for public use and consist of a wide variety of indicators where major progress was achieved to enable international comparisons. Besides those databases, an increasing number of international survey programs have been established within Europe (such as the Eurobarometer, the European Social Survey, the European Value Study) and beyond (such as the International Social Survey Program, the World Value Survey etc.) to provide public opinion data from citizens all over the world.
For every database and for every survey there are multidimensional requirements to guarantee a high level of quality. Statistical estimates should be as accurate as possible to enable clear insights of the empirical reality in every nation. The results should be available within tight-fitting time points to allow a close monitoring of societal change. The comparability of indicators, the equivalence of constructs, the relevance of concepts, the clarity of definitions, the coherence of data sources and the completeness of data are further issues which attract attention in research. In general, available datasets are designed by groups of experts but usually the process of gathering the data is contracted out to national institutes. Constraints in data quality thus always refer to the whole data gathering process and may be highly different between countries.
Questionnaire development: e.g. issues of translation and comparability
Specification of concepts for research: suitability and equivalence
Sampling frame: deviances with regard to the target population
Sampling strategy: best practice examples and national differences to achieve representative results
Nonresponse: strategies to increase response rates and to prevent item-nonresponse
Survey modes: different field work standards in various countries
Interviewer effects: e.g. partly faked and faked interviews
Measurement errors due to respondents (e.g. response styles)
Quality control procedures: inadequate institutional standards including unethical practices
Weighting and coding issues (e.g. organizing data for public use)
10月13日
2016
10月15日
2016
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