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What theories explain variation in public opinion toward asylum seekers? We implement a survey experiment in which a representative sample of German residents evaluates vignettes of asylum seekers, which randomly vary attributes that speak to deservingness, economic and religious threat, and gender considerations of attitude formation. We find strong support for deservingness theories. Economic and religious threat theories also receive empirical support. Gender plays a negligible role. Importantly, we also document that economic and—to a lesser extent—religious threat considerations only matter when respondents evaluate economic refugees. By contrast, political refugees are welcomed nearly unconditionally. Our paper thus replicates key findings from Bansak, Hainmueller, and Hangartner (2016) and Czymara and Schmidt-Catran (2016) using a representative sample and points to an important interaction effect in public opinion formation toward asylum seekers: economic threat only gets activated when refugees' deservingness is in doubt. [ABSTRACT FROM AUTHOR]

This paper addresses speeding, that is, "too fast" responses, in web surveys. Relying on the response process model, we argue that very short response times indicate low data quality, stemming from a lack of attention on the part of respondents. To identify speeding, prior research employed case-wise procedures. Using data from nine online surveys, we demonstrate that response behavior of individual respondents varies considerably during a survey. Thus, we use case- and page-wise procedures to capture speeding behavior that taps different, although related, phenomena. Moreover, page-specific speeding measures capture aspects of data quality that traditional quality measures do not cover. Employing both page-specific and case-wise speeding measures, we examine whether removing speeders makes a difference in substantive findings. The evidence indicates that removing "too fast" responses does not alter marginal distributions, irrespective of which speeder-correction technique is employed. Moreover, explanatory models yield, by and large, negligible coefficient differences (on average about one standard error). Only in exceptional cases differences exceed two standard errors. Our findings suggest that speeding primarily adds some random noise to the data and attenuate correlations, if it makes a difference at all. The paper concludes by discussing implications and limitations. [ABSTRACT FROM AUTHOR]

Real-time response (RTR) measurement is an important technique for analyzing human processing of electronic media stimuli. Although it has been demonstrated that RTR data are reliable and internally valid, some argue that they lack external validity. The reason for this is that RTR measurement is restricted to a laboratory environment due to its technical requirements. This paper introduces a smartphone app that 1) captures real-time responses using the dial technique and 2) provides a solution for one of the most important problems in RTR measurement, the (automatic) synchronization of RTR data. In addition, it explores the reliability and validity of mobile RTR measurement by comparing the real-time reactions of two samples of young and welleducated voters to the 2013 German televised debate. Whereas the first sample participated in a classical laboratory study, the second sample was equipped with our mobile RTR system and watched the debate at home. Results indicate that the mobile RTR system yields similar results to the lab-based RTR measurement, providing evidence that laboratory studies using RTR are externally valid. In particular, the argument that the artificial reception situation creates artificial results has to be questioned. In addition, we conclude that RTR measurement outside the lab is possible. Hence, mobile RTR opens the door for large-scale studies to better understand the processing and impact of electronic media content. [ABSTRACT FROM AUTHOR]

In survey research, a consensus has grown regarding the effectiveness of incentives encouraging survey participation across different survey modes and target populations. Most of this research has been based on surveys from the United States, whereas few studies have provided evidence that these results can be generalized to other contexts. This paper is the first to present comprehensive information concerning the effects of incentives on response rates and nonresponse bias across large-scale surveys in Germany. The context could be viewed as a critical test for incentive effects because Germany's population is among the most survey-critical in the world, with very low response rates. Our results suggest positive incentive effects on response rates and patterns of effects that are similar to those in previous research: The effect increased with the monetary value of the incentive; cash incentives affected response propensity more strongly than lottery tickets do; and prepaid incentives could be more cost effective than conditional incentives. We found mixed results for the effects of incentives on nonresponse bias. Regarding large-scale panel surveys, we could not unequivocally confirm that incentives increased response rates in later panel waves. [ABSTRACT FROM AUTHOR]

Fair evaluation of interviewers based on their cooperation rates is complicated in most surveys. Depending on the mode(s) of data collection and the methods used to assign sampled cases to interviewers, different interviewers often work cases that are more or less difficult to interview. Further, in centralized telephone facilities, interviewers are given cases affected by the results of earlier attempts by other interviewers. This paper proposes and evaluates an interviewer performance indicator that attempts to repair these weaknesses and can be used in all data collection modes involving interviewers. For each contact made by an interviewer, the deviation between the outcome of that contact (1 = successful interview, 0 = other) and the predicted probability of a successful interview for that contact (according to auxiliary information and survey paradata) is recorded. Each interviewer then receives a score that is the mean of these deviations across all contacts. This performance indicator gives larger credit to the interviewer who obtains success on difficult cases versus relatively easy cases. The indicator also gives smaller penalties to failures on very difficult cases. We analyze face-to-face and telephone contacts from three different surveys to illustrate the computation of this indicator and its properties. We find that calling-history paradata are the strongest predictors of obtaining interviews in both modes (especially for face-to-face contacts), and produce propensity-adjusted performance indicators that more effectively distinguish among interviewers. [ABSTRACT FROM PUBLISHER]

Yu, Tian, and Tang (2008) proposed two new techniques for asking questions on sensitive topics in population surveys: the triangular model (TM) and the crosswise model (CM). The two models can be used as alternatives to the well-known randomized response technique (RRT) and are meant to overcome some of the drawbacks of the RRT. Although Yu, Tian, and Tang provide a promising theoretical analysis of the proposed models, they did not test them. We therefore provide results from an experimental survey in which the crosswise model was implemented and compared to direct questioning. To our knowledge, this is the first empirical evaluation of the crosswise model. We focused on the crosswise model because it seems better suited than the triangular model to overcome the self-protective “no” bias observed for the RRT. This paper-and-pencil survey on plagiarism was administered to Swiss and German students in university classrooms. Results suggest that the CM is a promising data-collection instrument eliciting more socially undesirable answers than direct questioning. [ABSTRACT FROM PUBLISHER]