BCG {metaSEM} | R Documentation |
Dataset on the Effectiveness of the BCG Vaccine for Preventing Tuberculosis
Description
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).
Usage
data(BCG)
Details
A list of data with the following structure:
- Trial
Number of the trials
- Author
Authors of the original studies
- Year
Year of publication
- VD
Vaccinated group with disease
- VWD
Vaccinated group without the disease
- NVD
Not vaccinated group with disease
- NVWD
Not vaccinated group without the disease
- Latitude
Geographic latitude of the place where the study was done
- Allocation
Method of treatment allocation
- ln_OR
Natural logarithm of the odds ratio: log((VD/VWD)/(NVD/NVWD))
- v_ln_OR
Sampling variance of ln_OR: 1/VD+1/VWD+1/NVD+1/NVWD
- ln_Odd_V
Natural logarithm of the odds of the vaccinated group: log(VD/VWD)
- ln_Odd_NV
Natural logarithm of the odds of the not vaccinated group: log(NVD/NVWD)
- v_ln_Odd_V
Sampling variance of ln_Odd_V: 1/VD+1/VWD
- cov_V_NV
Sampling covariance between ln_Odd_V and ln_Odd_NV: It is always 0
- v_ln_Odd_NV
Sampling variance of ln_Odd_NV: 1/NVD+1/NVWD
Source
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.
References
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/.
Examples
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)