3 Things You Should NOT Do with Missing Data

QuantFish instructor and statistical consultant Dr. Christian Geiser discusses three common mistakes when dealing with missing data. See also references at the very bottom. #Mplus #statistics #SPSS #missingdata #mplusforbeginners #sem #cfa #regressionanalysis #fiml #mar #mcar #geiser #quantfish #statisticalanalysis #stats #statisticstutorials #dataanalysis FREE weekly stats tips: https://mailchi.mp/goquantfish.com/ne... FREE statistics workshops: https://www.goquantfish.com/collectio... Get Dr. Geiser's FREE MPLUS FOR BEGINNERS COURSE: https://www.goquantfish.com/courses/m... FREE MPLUS SAMPLE SIZE PLANNING & SIMULATION MINI-COURSE: https://www.goquantfish.com/courses/s... MISSING DATA HANDLING IN MPLUS COURSE: https://www.goquantfish.com/courses/m... CFA & SEM WITH MPLUS COURSE: https://www.goquantfish.com/courses/m... Dr. Geiser's BOOKS: ****Longitudinal Structural Equation Modeling with Mplus: https://amzn.to/3ekOLOW ****Data Analysis with Mplus: https://amzn.to/3eg9vY4 ON-DEMAND MPLUS COURSES: ****Mplus from Scratch: https://www.goquantfish.com/courses/m... ****Multilevel Modeling with Mplus: https://www.goquantfish.com/courses/m... ****Latent Class Analysis with Mplus: https://www.goquantfish.com/courses/l... GET IN TOUCH with DR. GEISER: ****Facebook:   / christiangeiserauthor   ****Website: https://christiangeiser.com ABOUT THIS INSTRUCTOR: Dr. Christian Geiser is a quantitative psychologist, author of two books on Mplus, and a leader in the development of latent variable techniques for complex data. With his accessible books and sought-after workshops, he has helped thousands of researchers and students around the world to achieve their analytic goals. Visit his website at christiangeiser.com. ABOUT QUANTFISH: We bring top-level stats training from the world's leading methodologists to researchers and students all over the world. Learn more at https://goquantfish.com. Some affiliate links may be included at no additional cost to purchasers. References Baraldi, A. N., & Enders, C. K. (2010). An introduction to modern missing data analyses. Journal of School Psychology, 48(1), 5-37. Enders, C. K. (2022). Applied missing data analysis (2nd ed.). New York: Guilford Publications. Graham, J. W. (2003). Adding missing-data-relevant variables to FIML-based structural equation models. Structural Equation Modeling, 10(1), 80-100. Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177.