Faculty

Wai CHAN

Qualifications:
Appointment:
Office:
Email:
Tel:
Fax:
Website:
Ph.D., UCLA
Associate Professor
Rm 340, Sino Building
wchan@cuhk.edu.hk
3943 6241
2603 5019
Quantitative Psychology Research Laboratory

Teaching Areas

2022-2023
  • PSYC4910- Senior Thesis Research I 
  • PSYC4920- Senior Thesis Research II 
  • PSYC6210- Resrch Issues in Clinical Psychology 
  • PSYC5010- Seminar in Research Methods I 
  • PSYC6010- Seminar in Research Methods II 

Research Interests

Structural equation modeling; multivariate statistics; resampling techniques; psychometric methods.

Publications

Representative

Kwan, J. L.-Y, & Chan W. (2011). Comparing standardized coefficients in structural equation modeling: A model reparameterization approach. Behavior Research Methods, 43, 730-745.

Chan, W. (2009). Bootstrap standard error and confidence intervals for the difference between two squared multiple correlation coefficients. Educational and Psychological Measurement, 69, 566-584.

Chan, W. (2007). Comparing indirect effects in structural equation modeling: A sequential model fitting method using covariance-equivalent specifications. Structural Equation Modeling, 14, 326-346.

Cheung, M. W.–L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. Psychological Methods, 10, 40-64.

Chan, W., & Chan, D. W.–L. (2004). The bootstrap standard error and confidence intervals for the correlation corrected for range restriction: A simulation study. Psychological Methods, 9, 369-385.

Chan, W. (2003). Analyzing ipsative data in psychological research. Behaviormetrika, 30(1), 99-121.

Chan, W., Ho, R. M., Leung, K., Chan, D. K., & Yung, Y.-F. (1999). An alternative method for the evaluation of congruence coefficients with Procrustes rotation: A bootstrap procedure. Psychological Methods, 4, 378-402.

Chan, W., & Bentler, P. M. (1998). Covariance structure analysis of ordinal ipsative data. Psychometrika, 63, 369-399.

© Copyright The Chinese University of Hong Kong- Psychology Department

Search