Ph.D. Ohio State University, 2010
Office: McGuinn 501
Scholarly Interests: Hao Wu's research interest lies in the evaluation of statistical models in psychology. Relying on tools such as classical asymptotic theories, Bayesian statistics and information theoretic methodologies, he is particularly interested in issues such as how to compare multiple statistical models, how to account for the fact that models are not exactly true in reality, and how to handle nonlinear relations or non-normal distributions.
Typically offered courses
Dong, L., Wu, H. and Waldman, I. (accepted). Measurement and structural invariance of the antisocial process screening device. Psychological Assessment.
Wu, H. and Neale, M. C. (2013). On the likelihood ratio tests in bivariate ACDE models. Psychometrika, 78(3), 441-463.
Wu, H. and Neale, M. C. (2012). Adjusted confidence intervals for a bounded parameter. Behavior Genetics, 42, 886-898.
Wu, H., Myung, I. J. and Batchelder, W. H. (2010a). Minimum description length model selection of multinomial processing tree models. Psychonomic Bulletin and Review, 17, 275-286.
Wu, H., Myung, I. J. and Batchelder, W. H. (2010b). On the complexity of multinomial processing tree models. Journal of Mathematical Psychology, 54, 291–303.
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