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We still cannot look inside people's heads. To measure emotions, opinions, evaluations, associations, and intentions, we have to ask people about these phenomena. Our data collection has changed over time, and many different methods are available. At present, Internet surveys are widely used in market research and are becoming an important data collection tool in universities. The main advantages of Internet surveys are the speed and cost reduction in comparison to more traditional data collection methods, the positive effect of self-administration, such as more privacy, use of more complex questionnaire routing, and in general a greater interactivity. Disadvantages are problems of Internet coverage of the general population, especially under-coverage of certain subgroups such as the elderly and the lower educated, and non-response. This contribution provides a review of existing studies comparing online surveys with more traditional data collection methods.

Whether computer assisted data collection methods should be used for survey data collection is no longer an issue. Most professional research organizations, commercial, government and academic, are adopting these new methods with enthusiasm. Computer assisted telephone interviewing (CATI) is most prevalent, and computer assisted personal interviewing (CAPI) is rapidly gaining in popularity. Also, new forms of electronic reporting of data using computers, telephones and voice recognition technology are emerging. This paper begins with a taxonomy of current computer assisted data collection methods. It then reviews conceptual and theoretical arguments and empirical evidence on such topics as: (1) respondents and interviewer acceptance of new techniques, (2) effect of computer assisted interviewing on data quality, (3) consequences for survey costs and (4) centralized vs. decentralized deployment of CATI.

Household survey nonresponse is a matter of concern in many countries. In one of the first
international trend analyses, de Leeuw and de Heer (2002) found that response rates declined
over the years, and that countries differed in response rates and nonresponse trends. Their
analyses cover longitudinal data on the Labour Force Survey from National Statistical
Institutes for the period 1980 to 1997. We added a new data set, covering the period 1998
-2015, and analysed nonresponse data over time and countries. In these analyses we
differentiated between voluntary and mandatory surveys. The trends visible in de Leeuw and
de Heer (2002) continue with possibly a small deceleration in refusal rates.

The robustness of J. de Jong-Gierveld's loneliness scale (with Van Tilburg, Theor G., Manual of the Loneliness Scale, 1986 [available from the authors]) was examined through analysis of data from 6 Dutch surveys using different modes of data collection (3 using self-administered paper questionnaires, 2 using face-to-face interviews, & 1 using telephone interviews). Among the findings are: collection mode did not affect robustness; questionnaires did not lead to higher item nonresponse; questionnaires & telephone interviews resulted in better interitem homogeneity & person scalability than face-to-face interviews; & absence of an interviewer did not result in greater self-disclosure & higher scale means. The robustness of the scale is discussed as questionable, however, in regard to interitem homogeneity & person scalability. 2 Tables, 50 References. Adapted from the source document.

Abstract. Most web surveys collect data through nonprobability or opt-in online panels, which are characterized by self-selection. A concern in online research is the emergence of professional respondents, who frequently participate in surveys and are mainly doing so for the incentives. This study investigates if professional respondents can be distinguished in online panels and if they provide lower quality data than nonprofessionals. We analyzed a data set of the NOPVO (Netherlands Online Panel Comparison) study that includes 19 panels, which together capture 90% of the respondents in online market research in the Netherlands. Latent class analysis showed that four types of respondents can be distinguished, ranging from the professional respondent to the altruistic respondent. A profile of professional respondents is depicted. Professional respondents appear not to be a great threat to data quality.

Recently, the leading position of telephone surveys as the major mode of data collection has been challenged. Telephone surveys suffer from a growing nonresponse, partly due to the general nonresponse trend for all surveys and partly due to changes in society and technology influencing contactability and willingness to answer. One way to counteract the increasing nonresponse is the use of an advance letter. In mail and face-to-face surveys, advance letters have been proven effective. Based on the proven effectiveness in face-to-face and mail surveys, survey handbooks advise the use of advance letters in telephone surveys. This study reviews the evidence for this advice and presents a quantitative summary of empirical studies on the effectiveness of advance letters in raising the response rate for telephone surveys. The major conclusion is that advance letters are also an effective tool in telephone surveys, with an average increase in response rate (RR1) from 58 percent (no letter) to 66 percent (advance letter), and an average increase in cooperation rate (COOP1) from 64 percent (no letter) to 75 percent (advance letter). Adapted from the source document.

Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Preface by Dr. Judith Tanur -- About the Companion Website -- Chapter 1 Probability Survey‐Based Experimentation and the Balancing of Internal and External Validity Concerns -- 1.1 Validity Concerns in Survey Research -- 1.2 Survey Validity and Survey Error -- 1.3 Internal Validity -- 1.4 Threats to Internal Validity -- 1.4.1 Selection -- 1.4.2 History -- 1.4.3 Instrumentation -- 1.4.4 Mortality -- 1.5 External Validity -- 1.6 Pairing Experimental Designs with Probability Sampling -- 1.7 Some Thoughts on Conducting Experiments with Online Convenience Samples -- 1.8 The Contents of this Book -- References -- Part I Introduction to Section on Within‐Unit Coverage -- Chapter 2 Within‐Household Selection Methods: A Critical Review and Experimental Examination -- 2.1 Introduction -- 2.2 Within‐Household Selection and Total Survey Error -- 2.3 Types of Within‐Household Selection Techniques -- 2.4 Within‐Household Selection in Telephone Surveys -- 2.5 Within‐Household Selection in Self‐Administered Surveys -- 2.6 Methodological Requirements of Experimentally Studying Within‐Household Selection Methods -- 2.7 Empirical Example -- 2.8 Data and Methods -- 2.9 Analysis Plan -- 2.10 Results -- 2.10.1 Response Rates -- 2.10.2 Sample Composition -- 2.10.3 Accuracy -- 2.11 Discussion and Conclusions -- References -- Chapter 3 Measuring Within‐Household Contamination: The Challenge of Interviewing More Than One Member of a Household -- 3.1 Literature Review -- 3.2 Data and Methods -- 3.2.1 The Partner Study Experimental Design and Evaluation -- 3.2.1.1 Effects on Response Rates and Coverage -- 3.3 The Sequence of Analyses -- 3.4 Results -- 3.4.1 Results of Experimental Group Assignment -- 3.5 Effect on Standard Errors of the Estimates -- 3.6 Effect on Response Rates.

An in-depth look at current issues, new research findings, and interdisciplinary exchange in survey methodology and processingSurvey Measurement and Process Quality extends the marriage of traditional survey issues and continuous quality improvement further than any other contemporary volume. It documents the current state of the field, reports new research findings, and promotes interdisciplinary exchange in questionnaire design, data collection, data processing, quality assessment, and effects of errors on estimation and analysis.The book's five sections discuss a broad range of issues and t

Abstract
There is an ongoing debate in the survey research literature about whether and when probability and nonprobability sample surveys produce accurate estimates of a larger population. Statistical theory provides a justification for confidence in probability sampling as a function of the survey design, whereas inferences based on nonprobability sampling are entirely dependent on models for validity. This article reviews the current debate about probability and nonprobability sample surveys. We describe the conditions under which nonprobability sample surveys may provide accurate results in theory and discuss empirical evidence on which types of samples produce the highest accuracy in practice. From these theoretical and empirical considerations, we derive best-practice recommendations and outline paths for future research.