Here's part of the abstract from Rios Morrison and Chung 2011, published in the Journal of Experimental Social Psychology:

In both studies, nonminority participants were randomly assigned to mark their race/ethnicity as either "White" or "European American" on a demographic survey, before answering questions about their interethnic attitudes. Results demonstrated that nonminorities primed to think of themselves as White (versus European American) were subsequently less supportive of multiculturalism and more racially prejudiced, due to decreases in identification with ethnic minorities.

So asking white respondents to select their race/ethnicity as "European American" instead of "White" influenced whites' attitudes toward and about ethnic minorities. The final sample for study 1 was a convenience sample of 77 self-identified whites and 52 non-whites, and the final sample for study 2 was 111 white undergraduates.

Like I wrote before, if you're thinking that it would be interesting to see whether results hold in a nationally representative sample with a large sample size, well, that was tried, with a survey experiment as part of the Time Sharing Experiments in the Social Sciences. Here are the results:

mc2011reanalysis

I'm mentioning these results again because in October 2014 the journal that published Rios Morrison and Chung 2011 desk rejected the manuscript that I submitted describing these results. So you can read in the Journal of Experimental Social Psychology about results for the low-powered test on convenience samples for the "European American" versus "White" self-identification hypothesis, but you won't be able to read in the JESP about results when that hypothesis was tested with a higher-powered test on a nationally-representative sample with data collected by a disinterested third party.

I submitted a revision of the manuscript to Social Psychological and Personality Science, which extended a revise-and-resubmit offer conditional on inclusion of a replication of the TESS experiment. I planned to conduct an experiment with an MTurk sample, but I eventually declined the revise-and-resubmit opportunity for various reasons.

The most recent version of the manuscript is here. Links to data and code.

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In the Political Behavior article, "The Public's Anger: White Racial Attitudes and Opinions Toward Health Care Reform", Antoine J. Banks presented evidence that "anger uniquely pushes racial conservatives to be more opposing of health care reform while it triggers more support among racial liberals" (p. 493). Here is how the outcome variable was measured in the article's reported analysis (p. 511):

Health Care Reform is a dummy variable recoded 0-1 with 1 equals opposition to reform. The specific item is "As of right now, do you favor or oppose Barack Obama and the Democrats' Health Care reform bill". The response options were yes = I favor the health care bill or no = I oppose the health care bill.

However, the questionnaire for the study indicates that there were multiple items used to measure opinions of health care reform:

W2_1. Do you approve or disapprove of the way Barack Obama is handling Health Care? Please indicate whether you approve strongly, approve somewhat, neither approve nor disapprove, disapprove somewhat, or disapprove strongly.

W2_2. As of right now, do you favor or oppose Barack Obama and the Democrats' Health Care reform bill?

[if "favor" on W2_2] W2_2a. Do you favor Barack Obama and the Democrats' Health Care reform bill very strongly, or not so strongly?

[if "oppose" on W2_2] W2_2b. Do you oppose Barack Obama and the Democrats' Health Care reform bill very strongly, or not so strongly?

The bold item above is the only item reported on as an outcome variable in the article. The reported analysis omitted results for one outcome variable (W2_1) and reported dichotomous results for the other outcome variable (W2_2) for which the apparent intention was to have a four-pronged outcome variable from oppose strongly to favor strongly.

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Here is the manuscript that I submitted to Political Behavior in March 2015 describing the results using the presumed intended outcome variables and a straightforward research design (e.g., no political discussion control, no exclusion of cases, cases from all conditions analyzed at the same time). Here's the main part of the main figure:

Banks2014Reproduction

The takeaway is that, with regard to opposition to health care reform, the effect of the fear condition on symbolic racism differed at a statistically significant level from the effect of the baseline relaxed condition on symbolic racism; however, contra Banks 2014, the effect of anger on symbolic racism did not differ at a statistically significant level from the effect of the relaxed condition on symbolic racism. The anger condition had a positive effect on symbolic racism, but it was not a unique influence.

The submission to Political Behavior was rejected after peer review. Comments suggested analyzing the presumed intended outcome variables while using the research design choices in Banks 2014. Using the model in Table 2 column 1 of Banks 2014, the fear interaction term and the fear condition term are statistically significant at p<0.05 for predicting the two previously-unreported non-dichotomous outcome variables and for predicting the scale of these two variables; the anger interaction term and the anger condition term are statistically significant at p<0.05 for predicting two of these three outcome variables, with p-values for the residual "Obama handling" outcome variable at roughly 0.10. The revised manuscript describing these results is here.

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Data are here, and code for the initial submission is here.

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Antoine Banks has published several studies on anger and racial politics (here, for example) that should be considered when making inferences about the substance of the effect of anger on racial attitudes. Banks had a similar article published in the AJPS, with Nicholas Valentino. Data for that article are here. I did not see any problems with that analysis, but I didn't look very hard, because the posted data were not the raw data: the posted data that I checked omitted, for example, the variables used to construct the outcome variable.

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