Daniel McNeish is an Associate Professor in the Quantitative Area in the Department of Psychology. Prior to ASU, he was an Assistant Professor in the Department of Methodology and Statistics at Utrecht University in the Netherlands, and a Research Scientist at UNC-Chapel Hill.
His research areas include multilevel models, longitudinal data analysis, analysis of small sample data, and structural equation models. His contributions to these areas have been acknowledged by the following,
He currently serves as an associate editor for Multivariate Behavioral Research, as a consulting editor for Psychological Methods and Behavior Research Methods, and is an editorial board member of Organizational Research Methods and the Routledge Multivariate Applications Book Series
For a full updated list of publications, please see my my personal website, https://sites.google.com/site/danielmmcneish/acdemic-work
Selected Publications
McNeish, D., Dumas, D.G., & Grimm, K.J. (2020). Estimating new quantities from longitudinal test scores to improve forecasts of future performance. Multivariate Behavioral Research
McNeish, D. & Hamaker, E.L. (2020). A primer on two-level dynamic structural equation modeling for intensive longitudinal data. Psychological Methods
McNeish, D. & Kelley, K. (2019). Fixed effects models versus mixed effects models for clustered data: Reviewing the approaches, disentangling the differences, and making recommendations. Psychological Methods, 24, 20-35.
McNeish, D. (2018). Thanks coefficient alpha, we’ll take it from here. Psychological Methods, 23, 412-433.
McNeish, D., An, J., & Hancock, G.R. (2018). The thorny relation between measurement quality and fit index cut-offs in latent variable models. Journal of Personality Assessment, 100, 43-52.
McNeish, D. & Matta, T. (2018). Differentiating between mixed effects and latent curve approaches to growth modeling. Behavior Research Methods, 50, 1398-1414.
McNeish, D., Stapleton, L. M., & Silverman, R.D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods, 22, 114-140.
McNeish, D. (2017). Small sample methods for multilevel modeling: A colloquial elucidation of REML and the Kenward-Roger correction. Multivariate Behavioral Research, 52, 661-670.
McNeish, D., & Wentzel, K.R. (2017). Accommodating small sample sizes in three level models when the third level is incidental. Multivariate Behavioral Research, 52, 200-215.
McNeish, D. & Dumas, D. (2017). Non-linear growth models as psychometric models: A second-order growth curve model for measuring potential. Multivariate Behavioral Research, 52, 61-85.
McNeish, D. (2017). Challenging conventional wisdom for multivariate statistical models with small samples. Review of Educational Research, 87, 1117-1151.
Dumas, D. & McNeish, D. (2017). Dynamic measurement modeling: Using nonlinear growth models to estimate student learning capacity. Educational Researcher, 46, 284-292.
McNeish, D., & Stapleton, L.M. (2016). The effect of small sample size on two level model estimates: A review and illustration. Educational Psychology Review, 28, 295-314.
McNeish, D., & Stapleton, L. M. (2016). Modeling clustered data with very few clusters. Multivariate Behavioral Research, 51, 495-518.
McNeish, D. (2016). On using Bayesian methods to address small sample problems. Structural Equation Modeling, 23, 750-773.
McNeish, D. (2015). Using Lasso for predictor selection and to assuage overfitting: A method long overlooked in behavioral sciences. Multivariate Behavioral Research, 50, 474-481.
McNeish, D. (2014). Modeling sparsely clustered data: Design-based, model-based, and single-level methods. Psychological Methods, 19, 552-563.
Fall 2020 | |
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Course Number | Course Title |
PSY 792 | Research |
Spring 2020 | |
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Course Number | Course Title |
PSY 230 | Introduction to Statistics |
PSY 792 | Research |
Fall 2019 | |
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Course Number | Course Title |
PSY 537 | Longitudinal Growth Modeling |
Spring 2019 | |
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Course Number | Course Title |
PSY 230 | Introduction to Statistics |
Fall 2018 | |
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Course Number | Course Title |
PSY 539 | Multilevel Models Psych Resrch |
Spring 2018 | |
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Course Number | Course Title |
GCU 593 | Applied Project |
Fall 2017 | |
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Course Number | Course Title |
PSY 539 | Multilevel Models Psych Resrch |