Results of logistic regression analyses predicting voting behavior from explicit and implicit prejudice and confidence.

Predicting votes for Mr. Obama (1) versus Mr. McCain (0) from explicit and implicit prejudice toward Blacks and their interactions with confidence. Controlling for date of implicit attitude measure administration. Model 1 examines explicit prejudice separately (N = 2,056). Model 2 examines implicit prejudice separately (N = 2,024). Model 3 examines both prejudice measures simultaneously (N = 2,024). CCC: correctly classified cases; B: regression weight B (log odds); SE: standard error of the regression weight B; Wald: Wald test statistic; OR: Odds ratio. Relative amount by which the odds increase (OR >1.0) or decrease (OR <1.0) when the value of the predictor is increased by 1 SD.

本数据集旨在基于对黑人的外显偏见（explicit prejudice）、内隐偏见（implicit prejudice）及其与自信程度的交互项，预测投票给奥巴马先生（标签赋值为1）与麦凯恩先生（标签赋值为0）的结果。分析过程中控制内隐态度测量的实施日期作为协变量。模型1单独考察外显偏见（样本量N=2056）；模型2单独考察内隐偏见（样本量N=2024）；模型3同时纳入两类偏见测量指标（样本量N=2024）。其中，CCC为正确分类样本数（correctly classified cases）；B为回归权重B（对数胜算比，log odds）；SE为回归权重B的标准误（standard error of the regression weight B）；Wald为Wald检验统计量（Wald test statistic）；OR为胜算比（Odds ratio），即当预测变量每增加1个标准差（SD）时，胜算提升（OR>1.0）或降低（OR<1.0）的相对幅度。