Attendees learned why principled methods of missing data handling are usually required to obtain unbiased estimates in long-running cohort studies.
The attendees were trained how to undertake such analyses, and gained practical experience of doing so themselves using Stata, with a focus on multiple imputation. The National Child Development Study (NCDS) was used throughout as a case study.
Attendees will learn why principled methods of missing data handling are usually required to obtain unbiased estimates in long-running cohort studies, learn how to undertake such analyses, and gain practical experience of doing so themselves using Stata, with a focus on multiple imputation. The National Child Development Study (NCDS) will be used throughout as a case study. There will be plenty of opportunity for questions and discussion.
By the end of the workshop, attendees will:
1. Understand why principled methods of missing data handling are usually required to obtain unbiased estimates in long-running cohort studies.
2. Understand why and how variables other than those included in the analysis should be included in principled methods of missing data handling.
3. Have gained familiarity with examples in which principled methods of missing data handling have been applied in the NCDS.
4. Have gained experience of applying such methods themselves in example applications using data from the NCDS (focusing on the use of multiple imputation in Stata).
The morning will consist of classroom-based learning, and the afternoon would involve a practical training session in the computer lab. Lunch will be provided.
The workshop will be run by staff from UCL Centre for Longitudinal Studies:
Richard Steele
Events and Marketing Officer
Phone: 020 7911 5320
Email: ioe.clsevents@ucl.ac.uk