See https://book.declaredesign.org/complex-designs.html#meta-analysis
Arguments
- data
A data frame with one row per study.
- yi
The bare column name of the study estimates.
- sei
The bare column name of their standard errors.
- method
character string to specify whether a fixed- or a random/mixed-effects model should be fitted. A fixed-effects model (with or without moderators) is fitted when using method = "FE". Random/mixed-effects models are fitted by setting method equal to one of the following: "DL", "HE", "SJ", "ML", "REML", "EB", "HS", "HSk", or "GENQ". Default is "REML".
- ...
Further arguments to
metafor::rma().
Value
An rma.uni fit; pass it to rma_mu_tau() to tidy it.
Details
Fits metafor::rma() to study-level estimates and standard errors. If the fit fails, it returns the error as an object rma_mu_tau() recognizes, so one failed simulation does not stop a diagnosis.
Examples
set.seed(343)
studies <- data.frame(
est = rnorm(10, mean = 0.2, sd = 0.1),
se = runif(10, min = 0.05, max = 0.15)
)
fit <- rma_helper(studies, yi = est, sei = se)
fit
#>
#> Random-Effects Model (k = 10; tau^2 estimator: REML)
#>
#> tau^2 (estimated amount of total heterogeneity): 0.0013 (SE = 0.0035)
#> tau (square root of estimated tau^2 value): 0.0367
#> I^2 (total heterogeneity / total variability): 17.27%
#> H^2 (total variability / sampling variability): 1.21
#>
#> Test for Heterogeneity:
#> Q(df = 9) = 9.7435, p-val = 0.3716
#>
#> Model Results:
#>
#> estimate se zval pval ci.lb ci.ub
#> 0.1384 0.0281 4.9166 <.0001 0.0832 0.1936 ***
#>
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>