Book contents
- The Cambridge Handbook of Implicit Bias and Racism
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Implicit Bias and Racism
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Taking Stock of Explicit and Implicit Prejudice
- 1 Report from the NSF Conference on Implicit Bias
- Section I What is Implicit Bias and (How) Can We Measure It?
- Section II Do Measures of Implicit Bias Predict Cognition and Behavior?
- Section III Challenges of Research on Implicit Bias
- Section IV Improving Measurement and Theorizing About Implicit Bias
- Introduction
- 15 Methodological Issues in the Study of Implicit Attitudes
- 16 The Bias of Crowds: Rethinking Implicit Bias in Social Context
- 17 Latent State–Trait Analyses for Process Models of Implicit Measures
- 18 Increasing the Validity of Implicit Measures: New Solutions for Assessment, Conceptualization, and Action Explanation
- 19 A Model of Moderated Convergence between Explicit Dispositions, Implicit Dispositions, and Behavior
- 20 Complications in Predicting Intergroup Behavior from Implicit Biases: One Size Does Not Fit All
- Section V How to Change Implicit Bias?
- Section VI Explicit Prejudice; Alive and Well?
- Section VII The Public’s (Mis)understanding of Implicit Bias
- Index
- References
17 - Latent State–Trait Analyses for Process Models of Implicit Measures
from Section IV - Improving Measurement and Theorizing About Implicit Bias
Published online by Cambridge University Press: 21 December 2024
Book contents
- The Cambridge Handbook of Implicit Bias and Racism
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Implicit Bias and Racism
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Taking Stock of Explicit and Implicit Prejudice
- 1 Report from the NSF Conference on Implicit Bias
- Section I What is Implicit Bias and (How) Can We Measure It?
- Section II Do Measures of Implicit Bias Predict Cognition and Behavior?
- Section III Challenges of Research on Implicit Bias
- Section IV Improving Measurement and Theorizing About Implicit Bias
- Introduction
- 15 Methodological Issues in the Study of Implicit Attitudes
- 16 The Bias of Crowds: Rethinking Implicit Bias in Social Context
- 17 Latent State–Trait Analyses for Process Models of Implicit Measures
- 18 Increasing the Validity of Implicit Measures: New Solutions for Assessment, Conceptualization, and Action Explanation
- 19 A Model of Moderated Convergence between Explicit Dispositions, Implicit Dispositions, and Behavior
- 20 Complications in Predicting Intergroup Behavior from Implicit Biases: One Size Does Not Fit All
- Section V How to Change Implicit Bias?
- Section VI Explicit Prejudice; Alive and Well?
- Section VII The Public’s (Mis)understanding of Implicit Bias
- Index
- References
Summary
A recent debate on implicit measures of racial attitudes has focused on the relative roles of the person, the situation, and their interaction in determining the measurement outcomes. The chapter describes process models for assessing the roles of the situation and the person-situation interaction on the one hand and stable person-related components on the other hand in implicit measures. Latent state-trait models allow one to assess to what extent the measure is a reliable measure of the person and/or the situation and the person-situation interaction (Steyer, Geiser, & Fiege, 2012). Moreover, trait factor scores as well as situation-specific residual factor scores can be computed and related to third variables, thereby allowing one to assess to what extent the implicit measure is a valid measure of the person and/or the situation and the person-situation interaction. These methods are particularly helpful when combined with a process decomposition of implicit-measure data such as a diffusion-model analysis of the IAT (Klauer, Voss, Schmitz, & Teige-Mocigemba, 2007).
Keywords
- Type
- Chapter
- Information
- The Cambridge Handbook of Implicit Bias and Racism , pp. 472 - 490Publisher: Cambridge University PressPrint publication year: 2025
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