76 2 Image 1 I analyze and present the data using marginal means because I compare different subgroups and wish to avoid confusing readers with different reference categories (Leeper et al., 2020). I present mostly voting likelihoods. A statistically significant finding does not majority preference for that attribute, but that an individual is more likely to vote for the a politician with that attribute (Abramson et al., 2022). When the outcomes in are consistent in all three countries, I present visuals of the pooled data, with separate visuals for each country in appendix 2. When I make statements about the general population, I use population weights to weight down the impact of respondents with a migration background to the proportion they are in the population. In all analyses, I cluster the standard errors at the level of the respondent. I prepared the data using R-package “tidyr” (Wickham, 2020), analyzed it using marginal means with R-package “cregg” (Leeper and Barnfield, 2020) and linear models using “miceadds” (Robitzsch et al., 2021), and visualized it with R-package “ggplot2” (Wickham et al., 2020). I pre-registered the hypotheses, see appendix 7 for an anonymized version of the pre-registration.
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