analyses:raudenbush2009
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analyses:raudenbush2009 [2020/06/26 06:51] – Wolfgang Viechtbauer | analyses:raudenbush2009 [2021/11/08 15:35] – Wolfgang Viechtbauer | ||
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dat | dat | ||
</ | </ | ||
- | (I copy the dataset into ' | + | (I copy the dataset into ''dat'', which is a bit shorter and therefore easier to type further below). The contents of the dataset are: |
<code output> | <code output> | ||
| | ||
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Note that there is a typo in Table 16.1 in the book chapter: The observed standardized mean difference for study 10 was $0.80$ and not $0.87$ (cf. Raudenbush and Bryk, 1985, Table 1). | Note that there is a typo in Table 16.1 in the book chapter: The observed standardized mean difference for study 10 was $0.80$ and not $0.87$ (cf. Raudenbush and Bryk, 1985, Table 1). | ||
- | ==== Fixed-Effects Model ==== | + | ==== Equal-Effects Model ==== |
The results from a model assuming homogeneous effects can now be obtained with: | The results from a model assuming homogeneous effects can now be obtained with: | ||
<code rsplus> | <code rsplus> | ||
- | res.FE <- rma(yi, vi, data=dat, digits=3, method=" | + | res.EE <- rma(yi, vi, data=dat, digits=3, method=" |
- | res.FE | + | res.EE |
</ | </ | ||
<code output> | <code output> | ||
- | Fixed-Effects Model (k = 19) | + | Equal-Effects Model (k = 19) |
- | Test for Heterogeneity: | + | I^2 (total heterogeneity / total variability): |
+ | H^2 (total variability / sampling variability): | ||
+ | |||
+ | Test for Heterogeneity: | ||
Q(df = 18) = 35.830, p-val = 0.007 | Q(df = 18) = 35.830, p-val = 0.007 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
- | Signif. codes: | + | Signif. codes: |
</ | </ | ||
These results match exactly what is reported in Table 16.2 (p. 301). In particular, $\hat{\theta} = 0.060$, | These results match exactly what is reported in Table 16.2 (p. 301). In particular, $\hat{\theta} = 0.060$, | ||
- | |||
- | **Sidenote**: | ||
==== Random-Effects Model ==== | ==== Random-Effects Model ==== | ||
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res.std <- list() | res.std <- list() | ||
- | res.std$FE <- rma(yi, vi, data=dat, digits=3, method=" | + | res.std$EE <- rma(yi, vi, data=dat, digits=3, method=" |
res.std$ML | res.std$ML | ||
res.std$REML <- rma(yi, vi, data=dat, digits=3, method=" | res.std$REML <- rma(yi, vi, data=dat, digits=3, method=" | ||
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<code output> | <code output> | ||
tau2 mu se | tau2 mu se | ||
- | FE 0.000 0.060 0.036 1.655 -0.011 0.132 | + | EE 0.000 0.060 0.036 1.655 -0.011 0.132 |
ML 0.013 0.078 0.047 1.637 -0.015 0.171 | ML 0.013 0.078 0.047 1.637 -0.015 0.171 | ||
REML 0.019 0.084 0.052 1.621 -0.018 0.185 | REML 0.019 0.084 0.052 1.621 -0.018 0.185 | ||
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res.knha <- list() | res.knha <- list() | ||
- | res.knha$FE <- rma(yi, vi, data=dat, digits=3, method=" | + | res.knha$EE <- rma(yi, vi, data=dat, digits=3, method=" |
res.knha$ML | res.knha$ML | ||
res.knha$REML <- rma(yi, vi, data=dat, digits=3, method=" | res.knha$REML <- rma(yi, vi, data=dat, digits=3, method=" | ||
Line 274: | Line 275: | ||
<code output> | <code output> | ||
tau2 mu se | tau2 mu se | ||
- | FE 0.000 0.060 0.051 1.173 -0.048 0.168 | + | EE 0.000 0.060 0.051 1.173 -0.048 0.168 |
ML 0.013 0.078 0.059 1.311 -0.047 0.202 | ML 0.013 0.078 0.059 1.311 -0.047 0.202 | ||
REML 0.019 0.084 0.062 1.359 -0.046 0.213 | REML 0.019 0.084 0.062 1.359 -0.046 0.213 | ||
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res.hw <- list() | res.hw <- list() | ||
- | res.hw$FE <- robust(res.std$FE, | + | res.hw$EE <- robust(res.std$FE, |
res.hw$ML | res.hw$ML | ||
res.hw$REML <- robust(res.std$REML, | res.hw$REML <- robust(res.std$REML, | ||
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HE 0.080 0.114 0.062 1.850 -0.015 0.244 | HE 0.080 0.114 0.062 1.850 -0.015 0.244 | ||
</ | </ | ||
- | Note that '' | + | Note that '' |
==== Final Note ==== | ==== Final Note ==== |
analyses/raudenbush2009.txt · Last modified: 2022/08/03 17:09 by Wolfgang Viechtbauer