Date(s) - 01/11/2021 - 02/08/2021
Based on Dr. Paul Allison’s book Missing Data, this on-demand seminar covers both the theory and practice of two modern methods for handling missing data: multiple imputation and maximum likelihood.
Many researchers have told us that they would love to take the course but just can’t manage the time or the money to attend the live sessions. Developed over three years, this web-based version is a popular alternative for anyone looking for a more flexible option to learn missing data techniques. It is designed to closely match the in-person version, but with substantial additional material.
The course takes place online in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 10 hours/week. You may participate at your own convenience; there are no set times when you are required to be online.
This four-week course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. It consists of 12 modules:
- Basic principles and assumptions.
- Conventional methods for missing data.
- Maximum likelihood (ML) for categorical variables.
- ML and the EM algorithm.
- Direct ML with SEM software and with mixed models.
- Basic principles of multiple imputation (MI).
- MI for non-monotone data using MCMC.
- MCMC options and complications.
- Fully conditional specification.
- Multivariate inference, interactions, and nonlinearities.
- Other methods, panel data, clustered data.
- Non-ignorable missing data.
This seminar will begin on Monday, January 11, 2021, and conclude on Monday, February 8, 2021.
All course materials are available 24 hours a day. Materials will be accessible for an additional 2 weeks after the official close on February 8.
The fee of $495 (USD) includes all course materials.
For more information on the event and to register, visit the page here.