analyses:vanhouwelingen2002
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionLast revisionBoth sides next revision | ||
analyses:vanhouwelingen2002 [2021/10/22 14:46] – Wolfgang Viechtbauer | analyses:vanhouwelingen2002 [2022/08/03 11:23] – Wolfgang Viechtbauer | ||
---|---|---|---|
Line 39: | Line 39: | ||
</ | </ | ||
- | ==== Fixed-Effects Model ==== | + | ==== Equal-Effects Model ==== |
- | The first model considered is the fixed-effects model based on the log odds ratios. The same model can be fitted with: | + | The first model considered is the equal-effects model based on the log odds ratios. The same model can be fitted with: |
<code rsplus> | <code rsplus> | ||
- | res <- rma(yi, vi, data=dat, method=" | + | res <- rma(yi, vi, data=dat, method=" |
res | res | ||
</ | </ | ||
<code output> | <code output> | ||
- | Fixed-Effects Model (k = 13) | + | Equal-Effects Model (k = 13) |
+ | |||
+ | I^2 (total heterogeneity / total variability): | ||
+ | H^2 (total variability / sampling variability): | ||
Test for Heterogeneity: | Test for Heterogeneity: | ||
Line 54: | Line 57: | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
- | Signif. codes: | + | Signif. codes: |
</ | </ | ||
For easier interpretation, | For easier interpretation, | ||
Line 120: | Line 123: | ||
</ | </ | ||
<code output> | <code output> | ||
- | | + | |
- | tau^2 0.3025 | + | tau^2 0.3025 |
- | tau 0.5500 | + | tau 0.5500 |
- | I^2(%) | + | I^2(%) |
H^2 | H^2 | ||
</ | </ | ||
Line 279: | Line 282: | ||
<code rsplus> | <code rsplus> | ||
res <- rma.mv(yi, vi, mods = ~ group - 1, random = ~ group | trial, struct=" | res <- rma.mv(yi, vi, mods = ~ group - 1, random = ~ group | trial, struct=" | ||
- | reg <- matreg(y=2, x=1, R=res$G, cov=TRUE, means=coef(res), | + | reg <- matreg(y=2, x=1, R=res$G, cov=TRUE, means=coef(res), |
reg | reg | ||
</ | </ | ||
<code output> | <code output> | ||
- | | + | |
- | intrcpt | + | intrcpt |
- | CON 0.7300 | + | CON 0.7300 |
--- | --- | ||
Line 293: | Line 296: | ||
Then Figure 5 in the paper (p. 605) can be recreated with: | Then Figure 5 in the paper (p. 605) can be recreated with: | ||
<code rsplus> | <code rsplus> | ||
- | tmp <- rma(measure=" | + | tmp <- rma(measure=" |
labbe(tmp, xlim=c(-8, | labbe(tmp, xlim=c(-8, | ||
points(coef(res)[1], | points(coef(res)[1], | ||
Line 315: | Line 318: | ||
abline(h=x[2]) | abline(h=x[2]) | ||
</ | </ | ||
+ | |||
+ | While the coefficient (i.e., 0.7300) of the relationship between the underlying true log odds in the vaccinated and unvaccinated groups obtained above is correct, the computation of the corresponding standard error is not quite right, as it assumes that the variance-covariance matrix used as input to '' | ||
+ | |||
+ | <code rsplus> | ||
+ | res <- rma.mv(yi, vi, mods = ~ group - 1, random = ~ group | trial, struct=" | ||
+ | </ | ||
+ | |||
+ | Now '' | ||
+ | |||
+ | <code rsplus> | ||
+ | res$vvc | ||
+ | </ | ||
+ | <code output> | ||
+ | tau^2.1 | ||
+ | tau^2.1 0.9359073 0.6711028 0.4822374 | ||
+ | cov | ||
+ | tau^2.2 0.4822374 0.4066553 0.3399395 | ||
+ | </ | ||
+ | |||
+ | We can then use this matrix as part of the input to '' | ||
+ | |||
+ | <code rsplus> | ||
+ | matreg(y=2, x=1, R=res$G, cov=TRUE, means=coef(res), | ||
+ | </ | ||
+ | |||
+ | <code output> | ||
+ | | ||
+ | intrcpt | ||
+ | CON 0.7300 | ||
+ | </ | ||
+ | |||
+ | Now the standard error of the coefficient of interest is computed in such a way that it correctly takes the imprecision of the estimates in '' | ||
==== Meta-Regression ==== | ==== Meta-Regression ==== |
analyses/vanhouwelingen2002.txt · Last modified: 2022/08/03 17:52 by Wolfgang Viechtbauer