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Imputation of systematic missing data in individual participant data meta-analysis

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  • Nicola Orsini

    (Karolinska Institutet)

Abstract

Answering research questions in light of multiple studies is challenged by one or more variables being 100% unobserved by design, also known as systematic missing data.The current imputation methods implemented in mi, however, are mainly suited for one study and sporadically missing data. Our aim is introduce a new user-deKned imputation method within mi impute capable of handling the main features of individual participant data (IPD) meta- analysis. Realistic simulated studies will be used to illustrate the logic and practice of imputing systematic missing data.

Suggested Citation

  • Nicola Orsini, "undated". "Imputation of systematic missing data in individual participant data meta-analysis," Northern European Stata Conference 2023 03, Stata Users Group.
    • Handle: RePEc:boc:neur23:03
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    File URL: http://repec.org/neur2023/Northern_Europe23_Orsini.pdf
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