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Supplements

Below are some supplement files of some of the papers we have written.

Gonzalez, O. & Valente, M. J. (2023). Accommodating a latent XM interaction in statistical mediation analysis. Multivariate Behavioral Research, 28, 659-674. DOI: 10.1080/00273171.2022.2119928

Gonzalez, O. (in press). Summary intervals for model-based classification accuracy and consistency indices. Educational and Psychological Measurement. DOI: 10.1177/00131644221092347

Gonzalez, O., Georgeson, A. R., Pelham, W. E. III., & Fouladi, R. T. (2021). Estimating classification consistency of screening measures and quantifying the impact of measurement bias. Psychological Assessment. DOI: 10.1037/pas0000938.

Gonzalez, O. (2021). Psychometric and machine learning approaches for diagnostic assessment and tests of individual classification. Psychological Methods. DOI: 10.1037/met0000317.

Gonzalez, O. (2021). Psychometric and machine learning approaches to reduce the length of scales. Multivariate Behavioral Research. DOI: 10.1080/00273171.2020.1781585.

Gonzalez, O. & MacKinnon, D. P. (2021). The measurement of the mediator and its influence on statistical mediation conclusions. Psychological Methods, 26, 1-17. DOI: 10.1037/met0000263.

Gonzalez, O., MacKinnon, D. P., & Muniz, F. B., (2021). Extrinsic convergent validity evidence to prevent Jingle and Jangle fallacies. Multivariate Behavioral Research, 56, 3-19. DOI: 10.1080/00273171.2019.1707061.

Gonzalez, O. & Pelham, W. E. III. (2021). When does differential item functioning matter for screening? A method for empirical evaluation. Assessment, 28, 446-456. DOI: 10.1177/1073191120913618.

Gonzalez, O., O’Rourke, H. P., Wurpts, I. C., & Grimm, K. J. (2018). Analyzing Monte Carlo simulation studies with Classification and Regression Trees. Structural Equation Modeling: A Multidisciplinary Journal, 25, 403-413. DOI: 10.1080/10705511.2017.1369353