Fr. 220.00

Mixed Methods for Psychological Measurement - Using Critical Realism to Reframe Incommensurability

English · Hardback

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Description

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This book presents a groundbreaking approach to measurement from a mixed methodological perspective, reframing the concept of incommensurability to harmonize qualitative and quantitative data in analyses.
It draws upon critical realism, latent variable theory, and phenomenography to illustrate how idiographic data can be incorporated into the development and validation of psychological measures. The text delves into foundational methodological assumptions, explores item and instrument validation techniques, and addresses issues of invariance. It further elucidates the application of idiographic strategies in conjunction with differential item function (DIF), item parameter drift (IPD), latent growth models, and the evaluation of measurement models. This innovative framework offers researchers robust tools for integrating diverse data types, enhancing the validity and reliability of their findings, and articulates ways in which these tools can be integrated into critical quantitative perspectives. It is an invaluable resource for anyone seeking to deepen their understanding of mixed methodologies and measurement.
It will appeal to scholars, researchers, and students whose goals are to integrate different modes of data, examine alternative perspectives on measurement, and apply new tools to psychological and social research.

List of contents

1. Nomothetic and Idiographic 2. Measurement of and Influences on Latent Constructs 3. Normalizing Error in Categorical Measurement 4. Quantitative Member Checking 5. Idiographic Measures 6. Idiographic Moderation in Measurement Models 7. A Critical Turn

About the author

David F. Feldon is a Professor of Instructional Technology and Learning Sciences in the Emma Eccles Jones College of Education and Human Services at Utah State University, USA.

Summary

This book presents a groundbreaking approach to measurement from a mixed methodological perspective, reframing the concept of incommensurability to harmonize qualitative and quantitative data in analyses.

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