The coef function extracts the estimated model coefficients from objects of class "rma". For objects of class "summary.rma", the model coefficients, corresponding standard errors, test statistics, p-values, and confidence interval bounds are extracted.

# S3 method for rma
coef(object, ...)

# S3 method for summary.rma
coef(object, ...)

Arguments

object

an object of class "rma" or "summary.rma".

...

other arguments.

Value

Either a vector with the estimated model coefficient(s) or a data frame with the following elements:

estimate

estimated model coefficient(s).

se

corresponding standard error(s).

zval

corresponding test statistic(s).

pval

corresponding p-value(s).

ci.lb

corresponding lower bound of the confidence interval(s).

ci.ub

corresponding upper bound of the confidence interval(s).

When the model was fitted with the Knapp and Hartung (2003) method (i.e., test="knha" in the rma.uni function) or with test="t" in the rma.glmm and rma.mv functions, then zval is called tval in the data frame that is returned by the function.

References

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1--48. http://www.jstatsoft.org/v36/i03/.

See also

Examples

### meta-analysis of the log risk ratios using a mixed-effects model ### with two moderators (absolute latitude and publication year) res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, mods = ~ ablat + year, data=dat.bcg) coef(res)
#> intrcpt ablat year #> -3.545505079 -0.028011275 0.001907557
#> estimate se zval pval ci.lb #> intrcpt -3.545505079 29.09587983 -0.1218559 0.903013130 -60.57238164 #> ablat -0.028011275 0.01023404 -2.7370689 0.006198931 -0.04806963 #> year 0.001907557 0.01468382 0.1299088 0.896638598 -0.02687219 #> ci.ub #> intrcpt 53.481371479 #> ablat -0.007952924 #> year 0.030687307