Table E.1 reports the results of the concurrence model. The data for the concurrence model consist of decisions by 34 justices in 7,473 cases during the 1946 through 2015 terms. The dependent variable is each justice's decision to file a concurring opinion (1 = concurring opinion; 0 = no concurring opinion; N = 39, 793). Unless noted otherwise, the data were derived from the Supreme Court Database. Because the dependent variable is dichotomous and separate opinions by the same justice may be interdependent, I employ a multilevel logistic regression model with random intercepts for justice. The model includes the justices’ SCIPEs for the Big Five (Extraversion, Conscientiousness, Agreeableness, Neuroticism, and Openness), the SCIPEs for the majority opinion author (OA Extraversion, OA Conscientiousness, OA Agreeableness, OA Neuroticism, and OA Openness), and the following control variables:
• The number of amicus curie briefs filed in each case, standardized within the term the case was filed (Amici Attention), as well as an interaction term between this variable and Extraversion.
• Each justice's ideological disagreement with the direction of the Court's ruling (Justice Disagreement), measured as the justice's Segal–Cover ideology score if the Court issued a liberal ruling and the inverted Segal–Cover score if the Court issued a conservative ruling, as well as an interaction term between this variable and Conscientiousness.
• A dichotomous indicator for cases in which the Court issued a liberal ruling (Liberal Ruling), as well as an interaction term between this variable and Agreeableness.
• A dichotomous indicator taking on the value one for the chief justice and zero otherwise (Chief Justice).
• A dichotomous indicator taking on the value one for justices in their first term on the Court and zero otherwise (Freshman Justice).
• The score that resulted from a factor analysis of the number of legal issues raised and the number of legal provisions at issue in the case (Case Complexity).
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