Missing Data Methods

About

This intensive summer school course on Missing Data Methods is designed for researchers, data analysts, and statisticians who encounter missing data in their work. Missing data can significantly impact the validity of research findings and statistical analyses. This course will provide a comprehensive overview of the concepts, techniques, and best practices for handling missing data. Participants will learn about different types of missing data, the assumptions underlying various methods, and how to implement these methods using the R statistical software. The course will include a mix of lectures, hands-on exercises, and case studies to guarantee a practical understanding of the topics covered.

Register through our website.

Course leader

Adiaba Consulting Group

Target group

researchers, data analysts, and statisticians

Course aim

1. Identify different types of missing data and understand their implications.
2. Apply appropriate methods for handling missing data in different contexts.
3. Utilize statistical software to implement missing data techniques.
4. Evaluate the impact of missing data methods on the results of their analyses.
5. Develop strategies to prevent and address missing data in research designs.

Fee info