Abstract
In this chapter we discuss issues raised by missing data. In Sect. 6.1 we discuss how to explore the robustness of our inference to different assumptions about missing outcome measures, while in Sect. 6.2 we describe an imputation approach which may be used when a study does not report the precision.
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Notes
- 1.
Index o stands for observed.
- 2.
R code to generate the funnel plots is given in the web-appendix.
- 3.
See Fig. 6.1 for creation of dataset mdata.
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Schwarzer, G., Carpenter, J.R., Rücker, G. (2015). Missing Data in Meta-Analysis. In: Meta-Analysis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-21416-0_6
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