Suchergebnisse

In this paper, we leverage a 10-wave election panel to examine the relative and dynamic effects of voter evaluations of Bush, Palin, Biden, McCain, and Obama in the 2008 presidential election. We show that the effects of these political figures on vote choice evolves through the campaign, with the predictive effects of President Bush declining after the nominees are known, and the effects of the candidates (and Palin), increasing towards Election Day. In evaluating the relative effects of these political figures on individual-level changes in vote choice during the fall campaign, we also find that evaluations of the candidates and Sarah Palin dwarf that of President Bush. Our results suggest a Bayesian model of voter decision making in which retrospective evaluations of the previous administration might provide a starting point for assessing the candidates, but prospective evaluations based on information learned during the campaign helps voters to update their candidate preference. Finally, we estimate the 'Palin effect,' based on individual-level changes in favorability towards the vice-presidential nominee, and conclude that her campaign performance cost McCain just under 2% of the final vote share. [Copyright Elsevier Ltd.]

In this paper, we leverage a 10-wave election panel to examine the relative and dynamic effects of voter evaluations of Bush, Palin, Biden, McCain, and Obama in the 2008 presidential election. We show that the effects of these political figures on vote choice evolves through the campaign, with the predictive effects of President Bush declining after the nominees are known, and the effects of the candidates (and Palin), increasing towards Election Day. In evaluating the relative effects of these political figures on individual-level changes in vote choice during the fall campaign, we also find that evaluations of the candidates and Sarah Palin dwarf that of President Bush. Our results suggest a Bayesian model of voter decision making in which retrospective evaluations of the previous administration might provide a starting point for assessing the candidates, but prospective evaluations based on information learned during the campaign helps voters to update their candidate preference. Finally, we estimate the 'Palin effect,' based on individual-level changes in favorability towards the vice-presidential nominee, and conclude that her campaign performance cost McCain just under 2% of the final vote share. [Copyright Elsevier Ltd.]

Abstract
In today's competitive information environment, clicks are the currency of the digital media landscape. Clickbait journalism attempts to entice attention with provocative and sensational headlines, but what are the implications when public opinion polls are the hook? Does the use of survey clickbait—news stories that make misleading claims about public opinion—have implications for perceptions of the public, journalists, or the polling industry? In two survey experiments conducted in the United States, we find that exposure to apolitical survey clickbait that makes exaggerated claims about the incompetence of the American public undermines perceptions of their capacity for democratic citizenship. At the same time, we find no evidence that this type of survey clickbait damages the reputations of the media or polling industry, suggesting that the media may have perverse incentives to use low-quality polls or to misrepresent polling results to drive traffic.

Abstract
In many survey settings, population counts or percentages are available for some of the variables in the survey, for example, from censuses, administrative databases, or other high-quality surveys. We present a model-based approach to utilize such auxiliary marginal distributions in multiple imputation for unit and item nonresponse in complex surveys. In doing so, we ensure that the imputations produce design-based estimates that are plausible given the known margins. We introduce and utilize a hybrid missingness model comprising a pattern mixture model for unit nonresponse and selection models for item nonresponse. We also develop a computational strategy for estimating the parameters of and generating imputations with hybrid missingness models. We apply a hybrid missingness model to examine voter turnout by subgroups using the 2018 Current Population Survey for North Carolina. The hybrid missingness model also facilitates modeling measurement errors simultaneously with handling missing values. We illustrate this feature with the voter turnout application by examining how results change when we allow for overreporting, that is, individuals self-reporting that they voted when in fact they did not.

What are the political implications of domestic migration to the American South? Using the American National Election Studies, we track the changing dynamic of party identification and presidential voting among white southern in‐migrants and natives. Although it was once thought southern in‐migration from the rest of the country contributed to Republican ascendancy in the region, we find that is no longer true. In the 1970s and 1980s, white migrants to the South were more Republican than natives. Today, white southern in‐migrants are more likely to affiliate with the Democratic Party and vote Democratic, suggesting population change could ultimately shift the partisan balance in the region.

ABSTRACTAlthough much of what we know about political advertising comes from the study of television advertising alone, online advertising is an increasingly prominent part of political campaigning. Research on other online political communication—especially candidate websites, blogs, and social media—tends to conclude that these communications are aimed primarily at turning existing supporters into campaign donors, activists, and volunteers. Is a similar communication strategy found in online display ads—those ads placed adjacent to website content? In one of the first systematic analyses of the nature, content, and targets of online display advertising, we examined 840 unique online display ads from the 2012 presidential campaign. We show that the policy content, ad location, and interactive elements of the ads varied based on the audience, with persuasive appeals aimed at undecided or persuadable voters and engagement appeals aimed at existing supporters. Comparing ad content across candidates also found that each side focused on those issues for which the candidate had a strategic advantage. As a consequence, and in contrast to the conclusions of previous research that examines television advertising, we found minimal issue engagement in online advertising.

Panel studies typically suffer from attrition. Ignoring the attrition can result in biased inferences if the missing data are systematically related to outcomes of interest. Unfortunately, panel data alone cannot inform the extent of bias due to attrition. Many panel studies also include refreshment samples, which are data collected from a random sample of new individuals during the later waves of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by non-ignorable attrition while reducing reliance on strong assumptions about the attrition process. We present a Bayesian approach to handle attrition in two-wave panels with one refreshment sample and many categorical survey variables. The approach includes (1) an additive non-ignorable selection model for the attrition process; and (2) a Dirichlet process mixture of multinomial distributions for the categorical survey variables. We present Markov chain Monte Carlo algorithms for sampling from the posterior distribution of model parameters and missing data. We apply the model to correct attrition bias in an analysis of data from the 2007–08 Associated Press/Yahoo News election panel study.

AbstractRising costs and challenges of in-person interviewing have prompted major surveys to consider moving online and conducting live web-based video interviews. In this paper, we evaluate video mode effects using a two-wave experimental design in which respondents were randomized to either an interviewer-administered video or interviewer-administered in-person survey wave after completing a self-administered online survey wave. This design permits testing of both within- and between-subject differences across survey modes. Our findings suggest that video interviewing is more comparable to in-person interviewing than online interviewing across multiple measures of satisficing, social desirability, and respondent satisfaction.

Online surveys, particularly those that draw samples from online panels of experienced respondents, now comprise a large segment of the academic and commercial opinion research markets due to their low cost and flexibility. A growing literature examines the implications of online surveys for data quality, most commonly by comparing demographic and political characteristics of different samples. In this paper, we explore the possibility that personality may differentially influence the likelihood of participation in online and face-to-face surveys. We argue that individuals high in extraversion and openness to experience may be underrepresented, and those low in these traits overrepresented, in professionalized online panels given the solitary nature of repeated survey-taking. Since openness to experience in particular is associated with liberal policy positions, differences in this trait may bias estimates of public opinion derived from professionalized online panels. Using data from the 2012 and 2016 dual-mode American National Election Studies, we compare political preferences and personality traits across parallel face-to-face and online samples. Respondents in the online samples were, on average, less open to experience and more politically conservative on a variety of issues compared to their face-to-face counterparts. This was true especially in 2012, when online respondents were drawn from a large panel of experienced respondents. We also find openness to be negatively related to the number of surveys completed by these respondents. These results suggest that reliance on professionalized survey respondents, who comprise the vast majority of online survey samples, can bias estimates of many quantities of interest.