# My teaching

## Current academic year 2018-2019

- PL2131 Research and Statistical Methods I (undergraduate)
- PL5221 Analysis of Psychological Data using GLM (postgraduate)
- PL5222 Multivariate Statistics in Psychology (postgraduate)

## Courses taught in previous academic years

- PL1101E Introduction to Psychology (team teaching)
- PL2131 Research and Statistical Methods I (undergraduate)
- PL2132 Research and Statistical Methods II (undergraduate)
- PL5221 Analysis of Psychological Data using GLM (postgraduate)
- PL5222 Multivariate Statistics in Psychology (postgraduate)
- PL5223 Psychometrics and Psychological Testing (postgraduate)
- PL5225 Structural Equation Modeling (postgraduate)

## Thesis topics that I may supervise

My research area is quantitative psychology–the statistical modeling of psychological data. A related area is psychometrics. You may get familiar with the area of quantitative psychology by reading a few recent issues in the following journals.

- Behavior Research Methods
- British Journal of Mathematical and Statistical Psychology
- Educational and Psychological Measurement
- Journal of Educational and Behavioral Statistics
- Multivariate Behavioral Research
- Organizational Research Methods
- Psychological Methods
- Research Synthesis Methods
- Sociological Methodology
- Sociological Methods and Research
- Structural Equation Modeling: A Multidisciplinary Journal

I am interested in supervising topics in one of the followings areas.

**Meta-analysis**- Fixed- vs. random-effects models
- Methods addressing missing covariates
- Correction for artifacts, e.g., unreliability and range restriction
- Multivariate meta-analysis
- Three-level meta-analysis
- Robust test

*Background readings*:- Cheung, M.W.-L. (2015). metaSEM: An R Package for Meta-Analysis using Structural Equation Modeling.
*Frontiers in Psychology*,*5*(1521). doi:10.3389/fpsyg.2014.01521. - Cheung, M.W.-L. (2014). Modeling dependent effect sizes with three-level meta-analyses: A structural equation modeling approach.
*Psychological Methods*,*19*, 211-229. - Cheung, M.W.-L. (2013). Multivariate meta-analysis as structural equation models.
*Structural Equation Modeling*,*20*, 429-454. - Cheung, M.W.-L. (2008). A model for integrating fixed-, random-, and mixed-effects meta-analyses into structural equation modeling.
*Psychological Methods*,*13*, 182-202.

- Cheung, M.W.-L. (2015). metaSEM: An R Package for Meta-Analysis using Structural Equation Modeling.
**Meta-analytic structural equation modeling (MASEM)**- Evaluating goodness-of-fit indices in MASEM
- Applications of MASEM in applied settings
- Exploring heterogeneity in MASEM

*Background readings*:- Cheung, M.W.-L. (2014). Fixed- and random-effects meta-analytic structural equation modeling: Examples and analyses in R.
*Behavior Research Methods*,*46*29-40. - Cheung, M.W.-L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach.
*Psychological Methods*,*10*, 40-64. - Cheung, M. W.-L., & Cheung, S. F. (2016). Random-effects models for meta-analytic structural equation modeling: Review, issues, and illustrations.
*Research Synthesis Methods*,*7*(2), 140–155. - Cheung, M. W.-L., & Hafdahl, A. R. (2016). Special issue on meta-analytic structural equation modeling: Introduction from the guest editors.
*Research Synthesis Methods*,*7*(2), 112–120.

- Cheung, M.W.-L. (2014). Fixed- and random-effects meta-analytic structural equation modeling: Examples and analyses in R.
**Structural equation modeling**- Constructing confidence intervals with SEM approach
- Testing mediating effect
- Testing moderating effect
- Latent growth models

*Background readings*:- Cheung, M.W.-L. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects.
*Behavior Research Methods*,*41*, 425-438. - Cheung, M.W.-L. (2009). Constructing approximate confidence intervals for parameters with structural equation models.
*Structural Equation Modeling*,*16*, 267-294. - Cheung, M.W.-L. (2007). Comparison of methods of handling missing time-invariant covariates in latent growth models under the assumption of missing completely at random.
*Organizational Research Methods*,*10*, 609-634. - Cheung, M.W.-L. (2007). Comparison of approaches to constructing confidence intervals for mediating effects using structural equation models.
*Structural Equation Modeling*,*14*, 227-246. - Cheung, M.W.-L., & Chan, W. (2004). Testing dependent correlation coefficients via structural equation modeling.
*Organizational Research Methods*,*7*, 206-223.

- Cheung, M.W.-L. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects.
**Multilevel models in cross-cultural research**- Multilevel issues in cross-cultural research
- Structural equivalence between level-1 and level-2 constructs

*Background readings*:- Cheung, M.W.-L., & Au, K. (2005). Applications of multilevel structural equation modeling to cross-cultural research.
*Structural Equation Modeling*,*12*, 598-619. - Cheung, M.W.-L., Leung, K., & Au, K. (2006). Evaluating multilevel models in cross-cultural research: An Illustration with Social Axioms.
*Journal of Cross-Cultural Psychology*,*37*, 522-541.

- Cheung, M.W.-L., & Au, K. (2005). Applications of multilevel structural equation modeling to cross-cultural research.