update.rma {metafor} | R Documentation |
The function can be used to update and (by default) refit "rma"
models. It does this by extracting the call stored in the object, updating the call, and (by default) evaluating that call.
## S3 method for class 'rma' update(object, formula., ..., evaluate=TRUE)
object |
an object of class |
formula. |
changes to the formula. See ‘Details’. |
... |
additional arguments to the call, or arguments with changed values. |
evaluate |
logical to specify whether to evaluate the new call or just return the call. |
For objects of class "rma.uni"
, "rma.glmm"
, and "rma.mv"
, the formula.
argument can be used to update the set of moderators included in the model (see ‘Examples’).
If evaluate=TRUE
the fitted object, otherwise the updated call.
The present function is based on update.default
, with changes made by Wolfgang Viechtbauer (wvb@metafor-project.org) so that the formula updating works with the (somewhat non-standard) interface of the rma.uni
, rma.glmm
, and rma.mv
functions.
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
rma.uni
, rma.mh
, rma.peto
, rma.glmm
, and rma.mv
for functions to fit models which can be updated / refit.
### calculate log risk ratios and corresponding sampling variances dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg) ### fit random-effects model (method="REML" is default) res <- rma(yi, vi, data=dat, digits=3) res ### fit mixed-effects model with two moderators (absolute latitude and publication year) res <- update(res, ~ ablat + year) res ### remove 'year' moderator res <- update(res, ~ . - year) res ### fit model with ML estimation update(res, method="ML") ### example with rma.glmm() res <- rma.glmm(measure="OR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, digits=3) res <- update(res, mods = ~ ablat) res ### fit conditional model with approximate likelihood update(res, model="CM.AL")