Re-assessing the incremental predictive validity of Implicit Association Tests

This project will examine the ability of the Implicit Association Test (IAT) to predict outcomes above and beyond explicit attitudes using Structural Equation Modeling (SEM). SEM allows for tests of incremental predictive validity while avoiding some of the issues of ordinary least squares regression with regard to false positives (OLS regression has been the primary model for testing the incremental predictive validity of the IAT in the past).

本项研究旨在探讨结构方程模型（SEM）在预测结果方面超越显性态度的隐式联想测验（IAT）的能力。结构方程模型能够进行增量预测效度的测试，同时避免了一些普通最小二乘回归（OLS regression）在假阳性方面的问题。在以往，OLS回归一直是检验IAT增量预测效度的主要模型。