我应该如何对metaforrma包中的函数进行语法处理，以便在以下小型元分析的真实示例中获得结果？（随机效应，汇总统计 SMD）
study, mean1, sd1, n1, mean2, sd2, n2
Foo2000, 0.78, 0.05, 20, 0.82, 0.07, 25
Sun2003, 0.74, 0.08, 30, 0.72, 0.05, 19
Pric2005, 0.75, 0.12, 20, 0.74, 0.09, 29
Rota2008, 0.62, 0.05, 24, 0.66, 0.03, 24
Pete2008, 0.68, 0.03, 10, 0.68, 0.02, 10
创建一个适当的data.frame：
df <- structure(list(study = structure(c(1L, 5L, 3L, 4L, 2L), .Label = c("Foo2000",
"Pete2008", "Pric2005", "Rota2008", "Sun2003"), class = "factor"),
mean1 = c(0.78, 0.74, 0.75, 0.62, 0.68), sd1 = c(0.05, 0.08,
0.12, 0.05, 0.03), n1 = c(20L, 30L, 20L, 24L, 10L), mean2 = c(0.82,
0.72, 0.74, 0.66, 0.68), sd2 = c(0.07, 0.05, 0.09, 0.03,
0.02), n2 = c(25L, 19L, 29L, 24L, 10L)), .Names = c("study",
"mean1", "sd1", "n1", "mean2", "sd2", "n2"), class = "data.frame", row.names = c(NA,
-5L))
运行rma-函数：
library(metafor)
rma(measure = "SMD", m1i = mean1, m2i = mean2,
sd1i = sd1, sd2i = sd2, n1i = n1, n2i = n2,
method = "REML", data = df)
请注意，rma假设(m1i-m2i). 这导致以下单变量随机效应模型荟萃分析：
> rma(measure = "SMD", m1i = mean1, m2i = mean2,
+ sd1i = sd1, sd2i = sd2, n1i = n1, n2i = n2,
+ method = "REML", data = df)
Random-Effects Model (k = 5; tau^2 estimator: REML)
tau^2 (estimate of total amount of heterogeneity): 0.1951 (SE = 0.2127)
tau (sqrt of the estimate of total heterogeneity): 0.4416
I^2 (% of total variability due to heterogeneity): 65.61%
H^2 (total variability / within-study variance): 2.91
Test for Heterogeneity:
Q(df = 4) = 11.8763, p-val = 0.0183
Model Results:
estimate se zval pval ci.lb ci.ub
-0.2513 0.2456 -1.0233 0.3061 -0.7326 0.2300
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
您可能想要更改估计method，例如method = "DL"（但我会坚持使用REML）。