BCG | R Documentation |
This dataset includes 13 studies on the effectiveness of the Bacillus Calmette-Guerin (BCG) vaccine for preventing tuberculosis (see van Houwelingen, Arends, & Stijnen (2002) for details).
data(BCG)
A list of data with the following structure:
Number of the trials
Authors of the original studies
Year of publication
Vaccinated group with disease
Vaccinated group without the disease
Not vaccinated group with disease
Not vaccinated group without the disease
Geographic latitude of the place where the study was done
Method of treatment allocation
Natural logarithm of the odds ratio: log((VD/VWD)/(NVD/NVWD))
Sampling variance of ln_OR: 1/VD+1/VWD+1/NVD+1/NVWD
Natural logarithm of the odds of the vaccinated group: log(VD/VWD)
Natural logarithm of the odds of the not vaccinated group: log(NVD/NVWD)
Sampling variance of ln_Odd_V: 1/VD+1/VWD
Sampling covariance between ln_Odd_V and ln_Odd_NV: It is always 0
Sampling variance of ln_Odd_NV: 1/NVD+1/NVWD
Colditz, G. A., Brewer, T. F., Berkey, C. S., Wilson, M. E., Burdick, E., Fineberg, H. V., & Mosteller, F. (1994). Efficacy of BCG vaccine in the prevention of tuberculosis: Meta-analysis of the published literature. Journal of the American Medical Association, 271, 698–702.
Berkey, C. S., Hoaglin, D. C., Mosteller, F., & Colditz, G. A. (1995). A random-effects regression model for meta-analysis. Statistics in Medicine, 14, 395–411.
van Houwelingen, H. C., Arends, L. R., & Stijnen, T. (2002). Advanced methods in meta-analysis: Multivariate approach and meta-regression. Statistics in Medicine, 21, 589–624.
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://www.jstatsoft.org/v36/i03/.
data(BCG)
## Univariate meta-analysis on the log of the odds ratio
summary( meta(y=ln_OR, v=v_ln_OR, data=BCG,
x=cbind(scale(Latitude,scale=FALSE),
scale(Year,scale=FALSE))) )
## Multivariate meta-analysis on the log of the odds
## The conditional sampling covariance is 0
bcg <- meta(y=cbind(ln_Odd_V, ln_Odd_NV), data=BCG,
v=cbind(v_ln_Odd_V, cov_V_NV, v_ln_Odd_NV))
summary(bcg)
plot(bcg)
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