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Abstract
This paper provides a discussion of the Tourangeau (2019) Morris Hansen Lecture paper. I address issues related to compounding errors in web surveys and the relationship between nonresponse and measurement errors. I provide a potential model for understanding when error sources in nonprobability web surveys may compound or counteract one other. I also provide three conceptual models that help explicate the joint relationship between nonresponse and measurement errors.

Survey researchers and practitioners use nonresponse adjustment weights to mitigate the effects of survey nonresponse on sample estimates. One challenge in creating these weights is finding useful auxiliary data that predict both the probability of participating in the survey and the survey variables of interest. This article reviews the use of paradata for nonresponse adjustment. Five different types of paradata are considered: neighborhood observations, observations of the sampled housing unit, observations of persons in the sampled housing unit, call records, and observations about the interviewer-householder interaction. Empirical evidence about the predictive value of these paradata for predicting both participation and survey variables is examined. Challenges of using these paradata are also identified, along with outstanding issues and opportunities related to the use of paradata for nonresponse adjustment. [Reprinted by permission of Sage Publications Inc., copyright The American Academy of Political and Social Science.]

Survey researchers and practitioners use nonresponse adjustment weights to mitigate the effects of survey nonresponse on sample estimates. One challenge in creating these weights is finding useful auxiliary data that predict both the probability of participating in the survey and the survey variables of interest. This article reviews the use of paradata for nonresponse adjustment. Five different types of paradata are considered: neighborhood observations, observations of the sampled housing unit, observations of persons in the sampled housing unit, call records, and observations about the interviewer-householder interaction. Empirical evidence about the predictive value of these paradata for predicting both participation and survey variables is examined. Challenges of using these paradata are also identified, along with outstanding issues and opportunities related to the use of paradata for nonresponse adjustment.

"Survey organizations rely on interviewers to make informed and efficient decisions about their efforts in the field, including which housing units they approach to knock on doors, make appointments, and obtain interviews. This paper presents initial findings from a feasibility test on a face to face survey, the US National Survey of Family Growth, in which the interviewers were equipped with GPS-enabled smartphones. This test included an experiment to determine if the use of the GPS-enabled smartphone altered interviewer behavior. We evaluate interviewer compliance with the GPS request, the effects of using the GPS device on interviewer behavior, and the quality of the recorded GPS points as related to interviewer behaviors. This test also included two surveys of interviewers that were completed after using the smartphone. We report results from these surveys and link one set of survey results to interviewer GPS compliance rates. Implications for future use of GPS devices to monitor and understand interviewer travel behavior are discussed." (author's abstract)

Abstract
Several questionnaire design texts emphasize a dual role of question wording: the wording needs to express what is being measured and tell respondents how to answer. Researchers tend to focus heavily on the first of these goals, but sometimes overlook the second, resulting in question wording that does not match the response options provided (i.e., mismatches). Common examples are yes/no questions with ordinal or nominal response options, open-ended questions with closed-ended response options, and check-all-that apply questions with forced-choice response options. A slightly different type of mismatch utilizes a question stem that can be read as asking for two different types of answers with no indication of which type should be provided. In this paper, we report the results of twenty-two experimental comparisons of data quality indicators (i.e., item nonresponse and response time) and response distributions across matched and mismatched versions of questions from a postal mail survey and a telephone survey. We find that mismatched items generally have lower data quality than matched items and that substantive results differ significantly across matched and mismatched designs, especially in the telephone survey. The results suggest that researchers should be wary of mismatches and should strive for holistic design.