metafor 包报告调整后的 R^2 还是正常的 R^2？
Does the metafor package report adjusted R^2 or just normal R^2?
我正在使用 R 中的 metafor 包进行元分析。比较使用 anova() 函数的模型，我可以看到 R^2。
fit1 <- rma(data = dat, yi, vi, mods = fix1)
fit2 <- rma(data = dat, yi, vi, mods = fix1 + fix2)
anova(fit1, fit2)
这是调整后的 R 平方还是普通的 R 平方？
谢谢。
请阅读 metafor 包中提供的文档。
https://cran.r-project.org/web/packages/metafor/metafor.pdf
对于函数anova.rma:
R2
amount of (residual) heterogeneity in the reduced model that is accounted for
in the full model (in percent). NA for fixed-effects models, if the amount of
heterogeneity in the reduced model is equal to zero, or for "rma.mv" objects.
This can be regarded as a pseudo R2
statistic (Raudenbush, 2009). Note that the
value may not be very accurate unless k is large (Lopez-Lopez et al., 2014).
我正在使用 R 中的 metafor 包进行元分析。比较使用 anova() 函数的模型，我可以看到 R^2。
fit1 <- rma(data = dat, yi, vi, mods = fix1)
fit2 <- rma(data = dat, yi, vi, mods = fix1 + fix2)
anova(fit1, fit2)
这是调整后的 R 平方还是普通的 R 平方？ 谢谢。
请阅读 metafor 包中提供的文档。
https://cran.r-project.org/web/packages/metafor/metafor.pdf
对于函数anova.rma:
R2
amount of (residual) heterogeneity in the reduced model that is accounted for in the full model (in percent). NA for fixed-effects models, if the amount of heterogeneity in the reduced model is equal to zero, or for "rma.mv" objects. This can be regarded as a pseudo R2 statistic (Raudenbush, 2009). Note that the value may not be very accurate unless k is large (Lopez-Lopez et al., 2014).