Measurement Error: Factors Influencing the Quality of Survey Data and Possible Corrections 2 |
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| Coordinator 1 | Dr Lydia Repke (GESIS - Leibniz Institute for the Social Sciences) |
| Coordinator 2 | Ms Fabienne Krämer (GESIS - Leibniz Institute for the Social Sciences) |
| Coordinator 3 | Dr Cornelia Neuert (GESIS - Leibniz Institute for the Social Sciences) |
High-quality survey data are the basis for meaningful data analysis and interpretation. The choice of specific survey characteristics (e.g., mode of data collection) and instrument characteristics (e.g., number of points in a response scale) affects data quality, meaning that there is always some measurement error. There are several methods and tools for estimating these errors (e.g., the Survey Quality Predictor) and approaches for correcting them in data analysis. This session will discuss factors that influence data quality, methods or tools for estimating their effects, and approaches for correcting measurement errors in survey data.
We invite papers that
(1) identify and discuss specific survey characteristics and their influence on data quality;
(2) identify and discuss specific instrument characteristics and their impact on data quality;
(3) discuss methods of estimating measurement errors and predicting data quality;
(4) present or compare tools for the estimation or correction of measurement errors;
(5) show how one can account for and correct measurement errors in data analysis.