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Evaluating the construct validity of Implicit Association Tests using Confirmatory Factor Analytic Models

机译:使用确认性因子分析模型评估内隐联想测验的构造效度

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摘要

The Implicit Association Test (IAT) is the most widely used method for assessing implicit bias and prejudice. By avoiding the need for introspection, the IAT is suggested to be a more valid indicator of prejudice than explicit measures of attitudes (i.e. questionnaires). However, implicit attitudinal literature has demonstrated highly variable associations between IAT scores and various outcomes. Such inconsistencies imply IAT scores may be significantly influenced by measurement error, which could thwart efforts to accurately estimate underlying attitudes. The aim of the present thesis was to examine the construct validity of the IAT using Confirmatory Factor Analytic models (CFA) to account for the confounding influences of measurement error.udThree studies examined various aspects of the validity of IATs using data from 198 student participants of the University of Tasmania, Australia. Study One assessed the internal consistency and internal convergent validity of traditional verbal IATs, fully pictorial IATs and Affective Priming Tasks (APTs) using single-group CFA. The study revealed high amount of random error variance in the implicit attitudinal data, comprising around 55% of IAT scores and 95% of APT scores. Despite the high proportion of random error, the IATs appeared to consistently assess the trait attitude constructs, though this was not true for the APTs. The APTs were consequently deemed invalid measures of implicit attitudes.
机译:隐性联想测验(IAT)是评估隐性偏见和偏见的最广泛使用的方法。通过避免进行内省,建议将IAT作为对偏见的明确衡量指标(即问卷)更有效的偏见指标。但是,隐性态度文献已证明IAT分数与各种结果之间存在高度可变的关联。这种不一致暗示IAT分数可能会受到测量误差的显着影响,这可能会阻碍准确估算基本态度的努力。本论文的目的是使用验证性因子分析模型(CFA)来检验IAT的结构效度,以解释测量误差的混杂影响。 ud三项研究使用来自198名学生的数据研究了IAT效度的各个方面。澳大利亚塔斯马尼亚大学。研究一使用单组CFA评估了传统口头IAT,完全图形IAT和情感启动任务(APT)的内部一致性和内部收敛有效性。该研究表明隐性态度数据中存在大量随机误差方差,包括IAT分数的55%和APT分数的95%。尽管随机错误所占比例很高,但IAT似乎能够始终如一地评估特质态度构造,尽管对于APT而言并非如此。因此,APT被认为是对内隐态度的无效衡量。

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    Chequer S;

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  • 年度 2014
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