The function extracts the estimated model coefficients, corresponding standard errors, test statistics, p-values (based on the permutation tests), and confidence interval bounds from objects of class "permutest.rma.uni".

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

Arguments

object

an object of class "permutest.rma.uni".

...

other arguments.

Value

A data frame with the following elements:

estimate

estimated model coefficient(s).

se

corresponding standard error(s).

zval

corresponding test statistic(s).

pval

p-value(s) based on the permutation test(s).

ci.lb

lower bound of the (permutation-based) confidence interval(s).

ci.ub

upper bound of the (permutation-based) confidence interval(s).

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

Author

Wolfgang Viechtbauer wvb@metafor-project.org http://www.metafor-project.org

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

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) ### permutation test # \dontrun{ pres <- permutest(res)
#> Running 1000 iterations for approximate permutation test.
coef(pres)# }
#> estimate se zval pval ci.lb ci.ub #> intrcpt -3.545505079 29.09587983 -0.1218559 0.911 -60.57238164 53.481371479 #> ablat -0.028011275 0.01023404 -2.7370689 0.017 -0.04806963 -0.007952924 #> year 0.001907557 0.01468382 0.1299088 0.906 -0.02687219 0.030687307