Title: Sample Size in Confirmatory Factor Analysis: And Other Related and Unrelated Adventures

Abstract: One of my persistent interests in quantitative methods is necessary or minimum sample size requirements for latent variable modelling. While there are superior methods for determining sample size requirements, such as power analysis or Monte Carlo methods, history suggests that these approaches may not gain wide-spread acceptance because they are not viewed as accessible by researchers. In my talk, I will cover some of my past attempts to address the question of minimum sample size requirements in latent variable modelling, as well as current plans. I will also briefly address two other research areas that interest me, reporting practices and academic entitlement.

Relevant Readings: Jackson (2003), Jackson, Voth & Frey (2013), Jackson, Gillaspy & Purc-Stephenson (2009)

Biography: Dennis Jackson received his Ph.D. at Wichita State University in Wichita, Kansas, in 1996. After a moderate stint where he was employed as an I/O Psychologist and researcher at a corporation in the U.S. he accepted a faculty position at the University of Windsor (2003), where he currently holds the position of Associate Professor. His research interests include sample size in confirmatory factor analysis, statistical practice and reporting, and academic entitlement. His hobbies include cycling and trying to keep up with a high-energy dog.