PD25-08 An Introduction to Missing Data Analyses for Educational Research

Session Type: Professional Development Course

Abstract

The mini-course titled “An Introduction to Missing Data Analyses for Educational Research” provides foundational knowledge about missing data analyses. The course content includes missing data assumptions, MCMC estimation, missing data imputation, incomplete categorical variables, and incomplete interaction effects. The course includes a mix of lecture and software demonstrations. Attendees will be provided with the following materials: lecture slides built around analysis examples from a real educational data set; free statistical analysis software, Blimp, developed by the instructors; a 100+ page white paper that provides details about a range of missing data topics; and a 250+ page annotated software tutorial guide that provides step-by-step instructions for 20 common statistical analyses. Because missing data are ubiquitous in educational research settings, the course content would appeal to virtually any educational discipline that relies on quantitative methods. The target audience includes graduate students, professors, and research professionals who use, but do not specialize in, quantitative methods. To maximize accessibility, the only prerequisite is a working knowledge of statistical concepts from a typical first-year graduate statistics sequence, in particular multiple regression. The course instructors, Craig Enders and Brian Keller, specialize in analytic issues related to missing data, and they co-develop the free software application Blimp, available at www.appliedmissingdata.com/blimp. There is an additional course fee: Member: $90/Non-member: $115

Sub Unit

• Professional Development and Training Committee

Directors

• Craig K. Enders, University of California - Los Angeles

• Brian T. Keller, University of Missouri

Instructor

• Remus Rose Mitchell, University of California - Los Angeles