Abstract
Survey research is the most frequently used data collection method in many disciplines. Nearly, everybody agrees that such data contain serious measurement errors. However, only few researchers try to correct for them. If the measurement errors in the variables vary, the comparison of the sizes of effects of these variables on each other will be wrong. If the sizes of the measurement errors are different across countries, cross-national comparisons of relationships between variables cannot be made. There is ample evidence for these differences in measurement errors across variables, methods and countries (Saris and Gallhofer in Design, evaluation and analysis of questionnaires for survey. Wiley, Hoboken, 2007; Oberski in Measurement errors in comparative surveys. PhD thesis, University of Tilburg, 2011). Therefore, correction for measurement errors is essential for the social sciences. The correction for measurement errors can be made in a simple way, but it requires that the sizes of the error variances are known for all observed variables. Many experiments are carried out to determine the quality of questions. The relationship between the quality and the characteristics of the questions has been studied. Because this relationship is rather strong, one can also predict the quality of new questions. A program SQP has been developed to predict the quality of questions. Using this program, the quality of the questions (complement of error variance) can be obtained for nearly all questions measuring subjective concepts. For objective variables, other research needs to be used (e.g., Alwin in Margins of error: a study of reliability in survey measurement. Wiley, Hoboken, 2007). Using these two sources of information, making correction for measurement error in survey research is possible. We illustrate here that correction for measurement errors can and should be performed.
Highlights
Most studies that require information of individual persons about values, attitudes, opinions, evaluations, feelings, preferences, expectations, status, occupation, education income and behavior rely on interviews or questionnaires
In order to predict the quality of new questions, the user has to code the characteristics of the question, and the program generates the prediction of the quality of the question. This means that researchers can get, via SQP, an estimate for most European Social Survey (ESS) and of other new questions without further costs than the required time to introduce the question in the program and to code it. This approach solves the major problem for the researchers: that one needs the estimates of the quality of all variables in the study in order to be able to correct for measurement error in the analysis
If one does not correct for measurement errors the consequences are, in general, that: 1. the relationships between variables are underestimated 2. the estimates of effects of different variables can be very biased and lead to wrong conclusions 3. the correlations across countries cannot be compared
Summary
Most studies that require information of individual persons about values, attitudes, opinions, evaluations, feelings, preferences, expectations, status, occupation, education income and behavior rely on interviews or questionnaires. The effects that the wording of survey questions can have on their responses have been studied in depth by many researchers; to mention some important contributions: Belson (1981), Schuman and Presser (1981), Sudman and Bradburn (1983), , Andrews (1984), Alwin and Krosnick (1991), Molenaar (1986), Költringer (1993), Scherpenzeel(1995), Tourangeau et al (2000), Dilmann (2000), Alwin (2007), Saris and Gallhofer (2007) and Biemer (2011). That is the same as saying that there is a considerable error in survey measurement even though in many cases we do not know what the true value of the variables we want to measure is While these studies are very well known to the research community and it is a very common opinion that survey data contain a lot of measurement errors, only very few researchers try to correct for these errors. We will discuss the three issues in sequence and come back to the general conclusions
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