Abstract
The current paper responds to the commentary on the article (doi:10.1002/jrsm.1605). We discuss our perspectives on the missing data mechanisms and models assumed and used in our simulation study while acknowledging the inherent generalizability limitations of any (simulation) study. The plausibility of the exact missing data mechanism is challenging to definitively identify in any applied dataset. We describe and justify our assumed scenario in meta-regression that we investigated. We also revisit the performance of the deletion method and how it is tied into the assumed missingness model. Lastly, we reiterate the importance of conducting sensitivity analyses assessing different ways of handling missing data given different assumptions and offer this study as a starting point for future research.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.