[R-meta] Moderator analysis with missing values (Methods and interpretations)
Tommy van Steen
tommyv@n@teen @ending from y@hoo@com
Fri Jul 6 14:36:58 CEST 2018
I’m running a meta-analysis using Cohen’s d in the metafor-package for R. I’m doubting my method/interpretation of results at various stages. As I want to make sure I’m doing it right, rather than doing what is convenient, I hope you could provide me with some advice regarding the following questions:
1. Heterogeneity is high in my data, and I want to add a list of moderators to test their influence. However, many of these moderators have missing values because not all studies have measured these variables. If I run a model that includes all moderators, the number of comparisons drops from 51 to 27. I’d prefer to include all moderators at once, but is this the right thing to do, or should I test each moderator separately?
2. Following 1: if I can run the model as a whole, is it possible and useful to in some way compare the overall effect size of the studies with no missing moderator data with those that are excluded in the model because of these missing datapoints?
3. Some moderators that are significant when including all moderators at once, are not significant when tested individually on the same subset of 27 studies. Which of the two statistics (as part of the larger model, or the individual moderator) should I report?
And two questions about interpretation:
4. I added publication year as moderator and and the estimate is 0.0360. Am I interpreting this result correctly when I say that every increase in the moderator year by 1, increases the effect size by 0.0360?
5. I also added a dichotomous moderator with options yes/no. In the moderator list, This moderator is listed with the ‘yes’ option, with an estimate of 0.5739, does this mean the effect size is 0.5739 higher than when the moderator value is ‘no’?
Thank you in advance for your thoughts and advice.
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