Statistical modelling with missing data using multiple imputation
Carpenter, James (2009) Statistical modelling with missing data using multiple imputation. NCRM. (Unpublished)
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Abstract
Course aims: Develop an intuitive understanding of key concepts in the missing data literature; - Understand the basis of multiple imputation (MI), and its pros and cons relative to other approaches; - Discuss how to perform MI in practice, and avoid common pitfalls; - Learn how to frame and to carry out simple sensitivity analyses, and - Develop an awareness of current research questions.
Item Type: | Other |
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Uncontrolled Keywords: | LongR |
Subjects: | 1. Frameworks for Research and Research Designs > 1.8 Longitudinal Research 3. Data Quality and Data Management > 3.6 Nonresponse > 3.6.1 Missing data 3. Data Quality and Data Management > 3.6 Nonresponse > 3.6.4 Imputation |
Depositing User: | NCRM users |
Date Deposited: | 22 Nov 2022 22:11 |
Last Modified: | 16 Jan 2023 12:31 |
URI: | https://eprints.ncrm.ac.uk/id/eprint/4776 |