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R script with data for MetaSEM forum.R [6] | 13.91 KB |
R script with data for MetaSEM forum.pdf [7] | 172.71 KB |
Dear Mike Cheung,
I am not a statistician and a beginner in meta-analysis. I'm struggling to perform an OSMASEM using the metaSEM r package. And I have a few questions.
1) I am not sure if the rate of missing data is not too high for some parameters and consequently if the results are reliable (and thus, if this research is publishable or not). Any suggestion if the rate of missing data is too high?
2) I hope I don't make any mistakes in my script and that I correctly performed the OSMASEM.
3) I use a categorical moderator. Is it appropriate to standardize this moderator? I think you wrote that moderator standardization improves numerical stability. should one not use standardization for continuous moderating variables only?
4) I have a moderating categorical variable (event valence) with two categories: "failure" vs "others" respectively coded -1 and 1.
The results of the OSMASEM with the moderator give several matrices. Is it right that:
A0 matrix gives betas for the model for the mean value of the moderator which may be meaningless (e.g., gender coded male -1 and female 1).
A1 matrix gives betas for the moderator effects on the parameters.
A0-A1 matrix gives in our case betas for the -1 ("failure") value of the moderator (-1 SD for continuous moderators)
A0+A1 matrix gives in our case betas for the +1 ("success") value of the moderator (+1 SD for continuous moderators)
5) I'm not sure why R2 can be higher than zero for a parameter (correlation) on which the moderator effect was not significant.
6) Imagine that I have a categorical moderator with three categories A, B and C coded 0, 1, and 2, respectively. Regarding the significance of the difference between the three categories, the OSMASEM with moderator tests the A category coded 0 versus the other two categories (B and C coded 1 and 2, respectively). Is it pertinent to change the code in order to test each category versus the other two? For example, with the same previous three categories A, B and C changing the code from 0, 1, and 2 to 1, 0, and 2 in order to test the difference between the category B (coded 0) versus the two others (A & C coded 1 and 2). I hope this last question is understandable.
Best regards,
L. B.