MVAC Tutorial
I gave a three-hour tutorial on Measurement Validation in Affective Computing at the Affective Computing and Intelligent Interaction (ACII 2023) conference in Boston, MA. Here are my slides:
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Recommended Articles
Cizek, G. J. (2016). Validating test score meaning and defending test score use: Different aims, different methods. Assessment in Education: Principles, Policy & Practice, 23(2), 212–225. https://doi.org/10.1080/0969594x.2015.1063479
Flake, J. K., & Fried, E. I. (2020). Measurement schmeasurement: Questionable measurement practices and how to avoid them. Advances in Methods and Practices in Psychological Science, 3(4), 456–465. https://doi.org/10/ghnbdg
Flake, J. K., Pek, J., & Hehman, E. (2017). Construct validation in social and personality research: Current practice and recommendations. Social Psychological and Personality Science, 8(4), 370–378. https://doi.org/10.1177/1948550617693063
Flora, D. B. (2020). Your coefficient alpha is probably wrong, but which coefficient omega is right? A tutorial on using R to obtain better reliability estimates. Advances in Methods and Practices in Psychological Science, 3(4), 484–501. https://doi.org/10.1177/2515245920951747
Gehlbach, H., & Brinkworth, M. E. (2011). Measure twice, cut down error: A process for enhancing the validity of survey scales. Review of General Psychology, 15(4), 380–387. https://doi.org/10/bnn2s3
Jacobucci, R., & Grimm, K. J. (2020). Machine Learning and Psychological Research: The Unexplored Effect of Measurement. Perspectives on Psychological Science, 15(3), 809–816. https://doi.org/10/ghdp3b
Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50(9), 741–749. https://doi.org/10.1037/0003-066x.50.9.741
Qiu, L., Chan, S. H. M., & Chan, D. (2017). Big data in social and psychological science: Theoretical and methodological issues. Journal of Computational Social Science, 1(1), 59–66. https://doi.org/10.1007/s42001-017-0013-6
ten Hove, D., Jorgensen, T. D., & van der Ark, L. A. (2022). Updated guidelines on selecting an intraclass correlation coefficient for interrater reliability, with applications to incomplete observational designs. Psychological Methods. https://doi.org/10.1037/met0000516
Weidman, A. C., Steckler, C. M., & Tracy, J. L. (2017). The jingle and jangle of emotion assessment: Imprecise measurement, casual scale usage, and conceptual fuzziness in emotion research. Emotion, 17(2), 267–295. https://doi.org/10.1037/emo0000226
Recommended Books
AERA, APA, & NCME. (2014). Standards for educational and psychological testing. American Educational Research Association. https://www.testingstandards.net/open-access-files.html
Bowden, S. C. (Ed.). (2017). Neuropsychological assessment in the age of evidence-based practice. Oxford University Press.
Brennan, R. L. (2001). Generalizability theory. Springer.
Gwet, K. L. (2021). Handbook of inter-rater reliability: Chance-corrected agreement coefficients (5th ed., Vol. 1).
Gwet, K. L. (2021). Handbook of inter-rater reliability: Analysis of quantitative ratings (5th ed., Vol. 2).
Kline, R. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Revelle, W. (2014). An introduction to psychometric theory with applications in R. https://www.personality-project.org/r/book/
Zumbo, B. D., & Hubley, A. M. (Eds.). (2017). Understanding and investigating response processes in validation research. Springer.