These and other related publications can be found on
Dr. Oswald’s Research Gate profile

 

 

Eby, L. T., Shockley, K. M., Bauer, T. N., Edwards, B. D., Homan, A. C., Johnson, R. E., Lang, J. W. B., Morris, S. B. & Oswald, F. L. (2020). Methodological checklists for improving research quality and reporting consistency. Industrial and Organizational Psychology: Perspectives on Science and Practice, 13, 76-83.

Braun, M. T., Converse, P. D., & Oswald, F. L. (2019). The accuracy of dominance analysis as a metric to assess relative importance: The joint impact of sampling error variance and measurement unreliability. Journal of Applied Psychology, 104, 593-602.

Banks, G. C., Field, J. G., Oswald, F. L., O’Boyle, E. H., Landis, R. S., Rupp, D. E., Rogelberg, S. G. (2019). Answers to 18 questions about open science practices. Journal of Business and Psychology, 3, 257-270.

Plonsky, L., & Oswald, F. L. (2017). Multiple regression as a flexible alternative to ANOVA in L2 research. Studies in Second Language Acquisition, 3, 579-592.

Heggestad, E. D., Rogelberg, S., Goh, A., & Oswald, F. L. (2015). Considering the effects of nonresponse on correlations between surveyed variables: A simulation study to provide context to evaluate survey results.  Journal of Personnel Psychology, 14, 91-103.

Zyphur, M. J., & Oswald, F. L. (2015). Bayesian estimation and inference: A user’s guide. Journal of Management, 41, 390-420.

Oswald, F. L., Converse, P. D., & Putka, D. J. (2014). Generating race, gender and other subgroup data in personnel selection simulations: A pervasive issue with a simple solution. International Journal of Selection and Assessment, 22, 310-320.

McAbee, S. T., Oswald, F. L., & Connelly, B. S. (2014). Bifactor models of personality and college student performance: A broad vs. narrow view. European Journal of Personality, 28, 604-619.

Plonsky, L., & Oswald, F. L. (2014). How big is ‘big’? Interpreting effect sizes in L2 research. Language Learning, 64, 878-912.

Nimon, K., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16, 650-674. [Also appears in Work and Organisational Psychology, 2015 (Boyle, O’Gorman, Fogarty, Eds.); SAGE Benchmarks in Psychology]

Nathans, L. L., Oswald, F. L., & Nimon, K. (2012). Multiple linear regression: A guidebook of variable importance. Practical Assessment, Research & Evaluation, 17, 1-19.

Braun, M., & Oswald, F. L. (2011). Exploratory regression analysis: A user-friendly tool for selecting models and determining predictor importance. Behavior Research Methods, 43, 331-339.

Imus, A., Schmitt, N., Kim, B., Oswald, F., Merritt, S., & Friede, A. (2011). Differential item functioning in biodata: Opportunity access as an explanation of gender- and race-related DIF. Applied Measurement in Education, 24, 1-24.

Oswald, F. L., & Hough, L. M. (2010). Validity in a jiffy: How synthetic validation contributes to personnel selection. Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 329-334.

Hönekopp, J., Becker, B. J., & Oswald, F. L. (2006). The meaning and suitability of various effect sizes for structured rater x ratee designs. Psychological Methods, 11, 72-86.

Ployhart, R. P., & Oswald, F. L. (2004). Applications of mean and covariance structure analysis: Integrating correlational and experimental approaches. Organizational Research Methods, 7, 27-65.

Oswald, F. L., Saad, S. A., & Sackett, P. R. (2000). The homogeneity assumption in differential prediction analysis: Does it really matter? Journal of Applied Psychology, 85, 536-541.