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Praise for theFirst Edition " ... this book is quite inspiring, giving many practical ideas for survey research, especially for designing better questionnaires."--International Statistical Review Reflecting modern developments in the field of survey research, the Second Edition of Design, Evaluation, and Analysis of Questionnaires for Survey Research continues to provide cutting-edge analysis of the important decisions researchers make throughout the survey design process. The new edition covers the essential methodologies and statistical tools utilized to create reliable and accurate survey questionnaires, which unveils the relationship between individual question characteristics and overall question quality. Since the First Edition, the computer program Survey Quality Prediction (SQP) has been updated to include new predictions of the quality of survey questions on the basis of analyses of Multi-Trait Multi-Method experiments. The improved program contains over 60,000 questions, with translations in most European languages. Featuring an expanded explanation of the usage and limitations of SQP 2.0, the Second Edition also includes: New practice problems to provide readers with real-world experience in survey research and questionnaire design A comprehensive outline of the steps for creating and testing survey questionnaires Contemporary examples that demonstrate the many pitfalls of questionnaire design and ways to avoid similar decisions Design, Evaluation, and Analysis of Questionnaires for Survey Research, Second Edition is an excellent textbook for upper-undergraduate and graduate-level courses in methodology and research questionnaire planning, as well as an ideal resource for social scientists or survey researchers needing to design, evaluate, and analyze questionnaires. Design, Evaluation, and Analysis of

This article attempts to explicate the subjective variable satisfaction with life in general by means of the objective variable income. The reason for this study is that, so far, the objective living conditions have been found to have little effect on the subjective feelings of people. Several different approaches have been used to estimate the strength of this relationship. First, correction for measurement errors was tried, then an alternative formulation of the relationship was tested using difference scores instead of the original variables. Next, nonlinear relationships between these variables were introduced. None of these methods led to any substantial strengthening of the relationship. Finally, a model was tested controlling for lagged variables and correcting for measurement errors in a panel design. The combination of these changes led to a considerable effect of the objective variable on satisfaction. This article shows how biased estimates of relationships can be. A specific combination of approaches led to a fundamentally different result.

Following the Treaty of Maastricht (Netherlands), the European Union (EU) entered a political crisis. Where held, public-demanded referenda over the treaty did not produce clear mandates for European integration. This was the first occasion on which politicians were confronted with strong opposition to European integration. Here, it is argued that such a crisis of political legitimation can recur at any time, because the general public lacks information about European policies, is generally not interested, & has no strong opinion. In this situation, public support for any kind of policy regarding European integration can be swayed rather easily as demonstrated via survey data from 1,691 adults in the Netherlands. 1 Table, 1 Appendix, 24 References. Adapted from the source document.

"It is well known fact that survey data contains always measurement errors, which can in different ways bias the results of the analyses (Alwin, 2007). In quantitative research this problem has been usually ignored due lack of quality estimates and complexity of correction procedure. Although this argument is not valid anymore, as there exists a new approach to determine quality of specific question, based on a prediction of the quality using the program SQP2, which in turn allows correcting for measurement error by following a relatively simple procedure (Saris & Revilla, 2015). During the recent years, there have been an increasing number of studies researching the structure of basic human values (Schwartz, 1992), which has resulted with improvements in the theory and led to a new 19-factor value model (Schwartz et al., 2012; Saris, Knoppen, & Schwartz, 2013). Although none of recent studies have considered the measurement error, which can potentially also have an effect on the structure. Therefor in this paper we will try to overcome this shortcoming and will be analysing the effect of the correction for measurement error on the structure of basic human values. We use same representative data from Estonia that was used in study of Lilleoja and Saris (2014), which enables to compare value structures before and after the correction for measurement error. Due to the existence of large ethnic minority in Estonian society, the sample allowed additionally testing the equivalence of the measurement in the two subpopulations after correcting for measurement error. This study shows that the correction for measurement error provides additional support for the validity of new value structure and it also shades some new light on the cross-cultural equivalence." (author's abstract)

Revilla and Saris compare a face-to-face and a web survey in terms of quality, defined as the strength of the relationships between the latent and the observed variables. The comparison is done between the European Social Survey (ESS), where the data is collected by face-to-face interviews at respondents' homes, and a study completed by the respondents of the Longitudinal Internet Studies for the Social Sciences (LISS) panel. Since the LISS is an online Dutch panel, whereas the ESS is conducted in many countries in order to avoid variations due to cultural or language differences, they focus only on the Netherlands. Adapted from the source document.