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[R-meta] About whether to delete the outliers from the dataset

Dear Nick,

It may be useful to add some additional context to your question for better
assistance.

For example, do you have a multilevel data structure where each study could
have multiple rows or instead you have allowed only one row for each study
in your dataset?

Also, can you possibly describe your method of outlier detection? For
instance, if you are using the metafor package, have you looked at the
combination of cooks.distance(), hatvalues(), and rstudent() for those
large effects in your meta-regression model?

Additionally, I wonder what happens to your pooled effect's standard error
(or the width of the pooled effect's confidence interval [CI]) with versus
without those large effects? For example, does the width of the CI
substantially (ex. by ~30%) decrease after removing those large effects,
increase, or remain largely unchanged?

Finally, depending on how much this matters to you in terms of your study
objectives, does retaining versus removing those large effects in your
meta-regression model change the statistical significance of your pooled
effect at all (i.e., sig. to not sig., or vice versa)?

Reza


On Sun, Dec 10, 2023 at 12:33?AM Nick Chen via R-sig-meta-analysis <
r-sig-meta-analysis at r-project.org> wrote: