Extract the Standard Errors from 'rma' Objects

Function to extract the standard errors from objects of class "rma".

se(object, ...)
# S3 method for default
se(object, ...)
# S3 method for rma
se(object, ...)

Arguments

object

an object of class "rma".

...

other arguments.

Value

A vector with the standard errors.

References

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03

See also

rma.uni, rma.mh, rma.peto, rma.glmm, and rma.mv for functions to fit models for which standard errors can be extracted.

Examples

### calculate log risk ratios and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### fit mixed-effects model with absolute latitude and publication year as moderators
res <- rma(yi, vi, mods = ~ ablat + year, data=dat)
res
#> 
#> Mixed-Effects Model (k = 13; tau^2 estimator: REML)
#> 
#> tau^2 (estimated amount of residual heterogeneity):     0.1108 (SE = 0.0845)
#> tau (square root of estimated tau^2 value):             0.3328
#> I^2 (residual heterogeneity / unaccounted variability): 71.98%
#> H^2 (unaccounted variability / sampling variability):   3.57
#> R^2 (amount of heterogeneity accounted for):            64.63%
#> 
#> Test for Residual Heterogeneity:
#> QE(df = 10) = 28.3251, p-val = 0.0016
#> 
#> Test of Moderators (coefficients 2:3):
#> QM(df = 2) = 12.2043, p-val = 0.0022
#> 
#> Model Results:
#> 
#>          estimate       se     zval    pval     ci.lb    ci.ub     
#> intrcpt   -3.5455  29.0959  -0.1219  0.9030  -60.5724  53.4814     
#> ablat     -0.0280   0.0102  -2.7371  0.0062   -0.0481  -0.0080  ** 
#> year       0.0019   0.0147   0.1299  0.8966   -0.0269   0.0307     
#> 
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 

### extract model coefficients
coef(res)
#>      intrcpt        ablat         year 
#> -3.545505079 -0.028011275  0.001907557 

### extract the standard errors
se(res)
#>     intrcpt       ablat        year 
#> 29.09587983  0.01023404  0.01468382