Assistant Professor
Office:
Scarfe Office Block 2321

Education:

University of British Columbia

Selected Publications:

Wu, A. D., Zumbo, B. D., Siegel, L. S. (2011). Piecewise general growth mixture modeling: Word recognition development for different learners in different phases. Journal of Modern Applied Statistical Methods, 10, 1, 226-248.

Wu, A. D., Begoray, D. L., MacDonald, M., Wharf-Higgins, J., Frankish, J., Kwan, B. Fung, W., &Rootman, I. (2010). Developing and evaluating a relevant and feasible instrument for measuring health literacy of Canadian high school students. Health Promotion International25, 4, 444-452.

Wu, A. D., Liu, Y., Gadermann, A. M., & Zumbo, B.D. (2010). Multiple-indicator multilevel growth model: A solution to multiple methodological challenges in longitudinal studies. Social Indicators Research: International Interdisciplinary Journal for Quality of Life Measurement, 97, 123-142.

Wu, A. D. & Zumbo, B. D. (2008).Understanding and using mediators and moderators.Social Indicators Research: An International Interdisciplinary Journal for Quality of Life Measurement87, 367–392.

Wu, A. D., Li, Z., & Zumbo, B. D. (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration With TIMSS Data. Practical Assessment Research & Evaluation12(2).Available online at http://pareonline.net/getvn.asp?v=12&n=2.

Research Projects:

Statistical methods for ordering the importance of variables: this line of research advances the use Pratt’s measures as a tool for assisting in interpreting modeling results.

Factors contributing to test item performance: this line of research studies the cognitive, linguistic, and emotional factors in item responding that contribute to the function and quality of test items.

Globalized testing through internet: this line of research studies the factors that can buffer response bias due to language, cultural differences, and self-report in the context of online globalized testing.

Methods for causal modeling: this line of research investigates statistical methods for making causal inferences in the absence of random experimental designs. A focus of this research is the methods for causal links such as mediation and moderation.

Courses Taught:

EPSE 423 Assessment of Classroom Learning
EPSE 481 Introduction to Research in Education
EPSE 482 Introduction to Statistics for Research in Education
EPSE 483 Reading and Interpreting Research in Education
EPSE 592 Experimental Designs and Analysis in Educational Research
EPSE 596 Correlational Designs and Analysis in Educational Research