Zhehan Jiang
November 7th, 2019 3:00-4:30 pm @ Gorgas Library 204F
Missing Data Imputations
Missing data are a common occurrence and can have a significant effect on the conclusions that can be drawn from the data. Removing observations with missing cells is proved to be an inefficient approach, which often introduces bias and reduces power. Imputation for missing data is an attractive method for handling missing data in numerous analyses. After this workshop, you will be able to know:
- Different missing mechanisms and data types
- Missing data solutions and their pros and cons
- Imputation technique and hands-on in R
- Procedures after imputation
Feel free to bring your laptop and install both R and Rstudio (https://www.andrewheiss.com/blog/2012/04/17/install-r-rstudio-r-commander-windows-osx/). Gorgas 204F has computers with R ready to be used as well.
About the Instructor
Dr. Zhehan Jiang is the Data Services Librarian and an Assistant Professor at the University of Alabama Libraries. He holds a PhD from the University Kansas, a Master’s degree from UCLA. He has published in Behavior Research Methods, Structural Equation Modeling, Applied Psychological Measurement, Educational and Psychological Measurement, Multivariate Behavioral Research, Psychometrika, and Methodology. His research focuses on cognitive diagnostic models, Bayesian statistics, applied deep learning, item response theory, and structural equation modeling.