David Stanley

• PhD The University of Western Ontario
• MA The University of Western Ontario
• BA University of Waterloo

Currently, I am interested in the statistical issues related to the replication crisis in psychology. In much of this research, I use Monte Carlo simulations to illustrate that beliefs about statistics/research processes commonly held by researchers are incorrect or have boundary conditions that limit generalizability. My I-O Psychology research interests include teamwork, organizational commitment, and the role of emotions in the workplace.

If you have a history of high grades in math/statistics, and are interested in Industrial-Organizational psychology, I encourage you to contact me as a potential graduate school advisor.

Replicability of Studies. Psychology is currently experiencing what some have called a 'crisis of confidence' due to the problems associated with replicating findings. I am interested in exploring the methodological factors that influence this issue.

Teamwork. Teams are being used extenstively within organizations, consequently they are the topic of a considerable amount of research. I am interested in the numerous methodological and statistical issues involved in team research.

Organizational Commitment. Individuals choose to remain at organizations for a variety of reasons. Those reasons include identification and emotional attachment (affective commitment), perceived obligation (normative commitment), and perceived costs of leaving (continuance commitment) (Meyer & Allen, 1990). Currently, I am collaborating with others to investigate how commitment levels and relations vary cross-culturally.

Emotions in the Workplace. Emotions are a key factor governing how individuals behave at both work and home. I am particularly interested in how various models of affect create different predictions for workplace behaviours.

Stanley, D. J., & Spence, J. R. (2024). The comedy of measurement errors: Standard error of measurement and standard error of estimation. Advances in Methods and Practices in Psychological Science, 7(4), 25152459241285885.

Spence, J. R., & Stanley, D. J. (2024). Tempered expectations: A tutorial for calculating and interpreting prediction intervals in the context of replications. Advances in Methods and Practices in Psychological Science, 7(1), 25152459231217932.

Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019). Failing Grade: 89% of Introduction-to-Psychology Textbooks That Define or Explain Statistical Significance Do So Incorrectly. Advances in Methods and Practices in Psychological Science.

Spence, J. R., & Stanley, D. J. (2018). Concise, Simple, and Not Wrong: In Search of a Short-Hand Interpretation of Statistical Significance. Frontiers in Psychology, 9, 2185.

Stanley, D. & Spence, J. (2018). Reproducible Tables in Psychology Using the apaTables Package. Advances in Methods and Practices in Psychological Science.

Spence, J. R., & Stanley, D. J. (2016). Prediction Interval: What to Expect When You’re Expecting… A Replication. PloS one, 11(9), e0162874.

Stanley, D. J., & Spence, J. R. (2014). Expectations for replications: Are yours realistic?. Perspectives on Psychological Science, 9(3), 305-318.

Allen, N.J., Stanley, D.J., Williams, H., & Ross, S.J. (2007b). Assessing Dissimilarity Relations Under Missing Data Conditions: Evidence from Computer Simulations. Journal of Applied Psychology, 92, 1414-1426.

Allen, N.J., Stanley, D.J., Williams, H., & Ross, S.J. (2007a). Assessing the Impact of Non-Response on Work Group Diversity Effects. Organizational Research Methods, 10, 262-286.

Meyer, J.P., Stanley, D. J., Herscovitch, L., Topolnytsky, L. (2002). Affective, continuance, and normative commitment to the organization: A meta-analysis of the antecedents, correlates, and consequences. Journal of Vocational Behavior, 61, 20-52.

Fall

PSYC*6060 Research Design & Statistics

PSYC*4780 Advanced Research Methods and Statistics

Winter

PSYC*3290 Conducting Statistical Analyses in Psychology

PSYC*6380 Psychological Applications of Multivariate Analysis