tips:computing_adjusted_effects
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tips:computing_adjusted_effects [2020/05/27 21:05] – Wolfgang Viechtbauer | tips:computing_adjusted_effects [2021/03/29 19:35] – Wolfgang Viechtbauer | ||
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===== Computing Adjusted Effects Based on Meta-Regression Models ===== | ===== Computing Adjusted Effects Based on Meta-Regression Models ===== | ||
- | After fitting a random-effects model and finding heterogeneity in the observed | + | 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 ' |
==== Data Preparation / Inspection ==== | ==== Data Preparation / Inspection ==== | ||
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</ | </ | ||
<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
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<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
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forest(res, xlim=c(-6.8, | forest(res, xlim=c(-6.8, | ||
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- | | + | |
text(-3.5, 15, " | text(-3.5, 15, " | ||
abline(h=0) | abline(h=0) | ||
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<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
1 0.60 0.25 1.41 0.14 2.57 | 1 0.60 0.25 1.41 0.14 2.57 | ||
2 0.38 0.23 0.64 0.10 1.38 | 2 0.38 0.23 0.64 0.10 1.38 | ||
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<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
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<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
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</ | </ | ||
<code output> | <code output> | ||
- | pred ci.lb ci.ub cr.lb cr.ub | + | pred ci.lb ci.ub pi.lb pi.ub |
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</ | </ |
tips/computing_adjusted_effects.txt · Last modified: 2023/09/11 16:10 by Wolfgang Viechtbauer