Welcome to CARMA’s Webcast Lecture

Aug. 26, 2022

Multiple Linear Regression: Strengthening Conceptual Knowledge and Practical Skills

12:00 PM – 1:30 PM ET

Dr. Fred Oswald is a professor at Rice University practicing in the area of Psychological Sciences. His main scopes of expertise ranges from Research Methods to Workforce Readiness and finally to Quantitative Methods (Meta-analysis, Psychometrics, Big Data). In 2020, Dr. Oswald was honored as a National Associate by the National Academy of Sciences . His recent published intellectual contributions are as follows:

Wu, F. Y., Mulfinger, E., Alexander, III, L., Sinclair, A. L., McCloy, R. A., & Oswald, F. L. (2022). Individual differences at play: An investigation into measuring Big Five facets with game-based assessments. International Journal of Selection and Assessment
Hysong, S. J., Arredondo, K., Hughes, A. M., Lester, H. F., Oswald, F. L., Petersen, L. A., et al. (2022). An evidence-based, structured, expert approach to selecting essential indicators of primary care quality
Bosnjak, M., Fiebach, C. J., Mellor, D., Mueller, S., O’Connor, D. B., Oswald, F. L., & SokolChang, R. I. (in press). A template for preregistration of quantitative research in psychology: Report of the Joint Psychological Societies Preregistration Task Force. American Psychologist

Abstract

Multiple linear regression (MLR) is one of the most useful and used methodological tools in the social sciences. This webinar will strengthen attendees’ conceptual knowledge and practical skills in MLR further through a series of topics presented: (a) relationships between descriptive statistics, visualization, and MLR; (b) conducting MLR with interaction and quadratic terms; (c) useful MLR reporting standards; and (d) MLR as the basis for path analysis, factor analysis (EFA, CFA, SEM), and multilevel modeling.

Readings

Farway, J. J., (2002). Practical regression and ANOVA using R.
Freedman, D. (1989). Statistical models and shoe leather. Mathematical Social Sciences, 18, 192-192.
Nimon, K., Oswald, F., & Roberts, J. K. (2013; 2020; 2021). yhat [Computer software and manual], Accessible from https://cran.r–project.org. Note: A package for the R statistics language and environment to interpret regression effects

Access Information

No registration is needed.
Login to your CARMA account.
Once you login, you will see a section “Active Meetings” under the “Access Live Events” tab.
Access link will be available one hour before the event in this section.