Evidence That an Ebola Outbreak Influenced Voting Preferences, Even After Controlling (Mindfully) for Autocorrelation: Reply to Tiokhin and Hruschka (2017)

“Did an Ebola outbreak influence the 2014 U.S. federal elections (and if so, how)? ” We addressed this question in a previous article (Beall, Hofer, & Schaller, 2016), in which analyses on preelection polling data were reported. Results indicated that the outbreak was associated with increased intentions to vote for conservative candidates and also increased inclination to conform to local voting norms. A Commentary by Tiokhin and Hruschka (2017) reports new analyses of these data after first detrending key variables. On the basis of these new results, Tiokhin and Hruschka’s Commentary concludes that there is “no evidence that an Ebola outbreak influenced voting preferences in the 2014 elections after controlling for time-series autocorrelation. ” The conclusion that there is “no evidence” is questionable, for two reasons. First, it does not take into account results (reported by Beall et al.) that did control for autocorrelation and did produce evidence linking the Ebola outbreak to changes in voting preferences. Second, the new analyses reported in Tiokhin and Hruschka’s Commentary have their own inferential shortcomings. Beall et al. reported two complementary analytic strategies to examine whether the Ebola outbreak was associated with changes in a voter-intention index. The primary strategy focused on the ongoing outbreak itself—treating the outbreak as an “intervention”—and compared preoutbreak and postoutbreak voterintention-index values. The second strategy did not focus directly on the outbreak but instead on Google searches for “Ebola”—treating an Ebola-search-volume index as an “assay” of the psychological salience of the outbreak—and examined correlations between the Ebola-search-volume index and the voter-intention index. (Americans searched for “Ebola” much more often during the month after the onset of the outbreak than they did before—which is why the Ebola-searchvolume index may have some inferential utility as an indicator of the outbreak.) Tiokhin and Hruschka’s Commentary focuses only on the second strategy. This omission matters because it is the first strategy (preoutbreak vs. postoutbreak comparison) that most directly addresses the research question (because it focuses explicitly on the outbreak, not on Internet search behavior), and it is within the context of that more direct strategy that Beall et al. did—in Study 1—report analyses that corrected for autocorrelation. Study 1 employed nationwide polling data to test whether the outbreak coincided with a change in Americans’ voting intentions. The results (depicted graphically in Beall et al., Fig. 1, p. 599) revealed that it did. There was a change in the temporal trajectory of the voter-intention index (a pattern that, within the politicalscience literature, has been labeled a wave effect; Shaw, 1999): Compared with the preoutbreak trajectory, the postoutbreak trajectory was toward greater support for conservative candidates—which indicates a cumulative impact of the ongoing outbreak. Beall et al. reported analyses that separately estimated preand postoutbreak trends. Results—which addressed inferential issues associated with autocorrelation—showed that the 718183 PSSXXX10.1177/0956797617718183Schaller et al.Reply to Tiokhin and Hruschka (2017) research-article2017