The metafor Package

A Meta-Analysis Package for R

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tips:comp_two_independent_estimates

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tips:comp_two_independent_estimates [2020/07/03 10:32] – Wolfgang Viechtbauertips:comp_two_independent_estimates [2021/11/08 15:49] – Wolfgang Viechtbauer
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 </code> </code>
  
-We can now compare the two estimates (i.e., the estimated average log risk ratios) by feeding them back to the ''rma()'' function and using the variable to distinguish the two estimates as a moderator. We use a fixed-effects model, because the (residual) heterogeneity within each subset has already been accounted for by fitting random-effects models above.+We can now compare the two estimates (i.e., the estimated average log risk ratios) by feeding them back to the ''rma()'' function and using the variable to distinguish the two estimates as a moderator. We use a fixed-effects meta-regression model for this purpose, because the (residual) heterogeneity within each subset has already been accounted for by fitting random-effects models above.
 <code rsplus> <code rsplus>
 rma(estimate, sei=stderror, mods = ~ meta, method="FE", data=dat.comp, digits=3) rma(estimate, sei=stderror, mods = ~ meta, method="FE", data=dat.comp, digits=3)
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 A discussion/comparison of these two approaches (i.e., assuming a single $\tau^2$ value or allowing $\tau^2$ to differ across subsets) can be found in the following article: A discussion/comparison of these two approaches (i.e., assuming a single $\tau^2$ value or allowing $\tau^2$ to differ across subsets) can be found in the following article:
  
-Rubio-Aparicio, M., López-López, J. A., Viechtbauer, W., Marín-Martínez, F., Botella, J., & Sánchez-Meca, J. (in press). A comparison of hypothesis tests for categorical moderators in meta-analysis using mixed-effects models. //Journal of Experimental Education//. [[https://www.tandfonline.com/doi/full/10.1080/00220973.2018.1561404|[Link]]]+Rubio-Aparicio, M., López-López, J. A., Viechtbauer, W., Marín-Martínez, F., Botella, J., & Sánchez-Meca, J. (2020). Testing categorical moderators in mixed-effects meta-analysis in the presence of heteroscedasticity. //Journal of Experimental Education, 88//(2), 288-310. [[https://doi.org/10.1080/00220973.2018.1561404]]
  
 We can also do a likelihood ratio test (LRT) to examine whether there are significant differences in the $\tau^2$ values across subsets. This can be done with: We can also do a likelihood ratio test (LRT) to examine whether there are significant differences in the $\tau^2$ values across subsets. This can be done with:
tips/comp_two_independent_estimates.txt · Last modified: 2024/04/18 11:36 by Wolfgang Viechtbauer