Differences

This shows you the differences between two versions of the page.

--- tips:computing_adjusted_effects [2020/06/26 06:47] – Wolfgang Viechtbauer
+++ tips:computing_adjusted_effects [2021/03/29 19:35] – Wolfgang Viechtbauer
@@ Line 1: / Line 1: @@
 ===== Computing Adjusted Effects Based on Meta-Regression Models =====
-After fitting a random-effects model and finding heterogeneity in the observed effects, meta-analysts often want to examine whether one or multiple moderator variables (i.e., predictors) are able to account for the heterogeneity (or at least part of it). Meta-regression models can be used for this purpose. A question that frequently arises in this context is how to compute an 'adjusted effect' based on such a model. This tutorial describes how to compute such adjusted effects for meta-regression models involving continuous and categorical moderators.
+After fitting a random-effects model and finding heterogeneity in the effects, meta-analysts often want to examine whether one or multiple moderator variables (i.e., predictors) are able to account for the heterogeneity (or at least part of it). Meta-regression models can be used for this purpose. A question that frequently arises in this context is how to compute an 'adjusted effect' based on such a model. This tutorial describes how to compute such adjusted effects for meta-regression models involving continuous and categorical moderators.
 ==== Data Preparation / Inspection ====
@@ Line 133: / Line 133: @@
 forest(res, xlim=c(-6.8,3.8), header=TRUE, atransf=exp,
        at=log(c(1/16, 1/8, 1/4, 1/2, 1, 2, 4, 8)), digits=c(2L,4L),
-       ilab=dat$ablat, ilab.xpos=-3.5, order=order(dat$ablat), ylim=c(-1.5,15))
+       ilab=dat$ablat, ilab.xpos=-3.5, order=dat$ablat, ylim=c(-1.5,15))
 text(-3.5, 15, "Lattitude", font=2)
 abline(h=0)