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- 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
- 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))
- library(metafor)
- rma(measure = "SMD", m1i = mean1, m2i = mean2,
- sd1i = sd1, sd2i = sd2, n1i = n1, n2i = n2,
- method = "REML", data = df)
- > 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
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