dat.collins1985a: Studies on the Treatment of Upper Gastrointestinal Bleeding...

dat.collins1985aR Documentation

Studies on the Treatment of Upper Gastrointestinal Bleeding by a Histamine H2 Antagonist

Description

Results from studies examining the effectiveness of histamine H2 antagonists (cimetidine or ranitidine) in treating patients with acute upper gastrointestinal hemorrhage.

Usage

dat.collins1985a

Format

The data frame contains the following columns:

id numeric study number
trial character first author of trial
year numeric year of publication
ref numeric reference number
trt character C = cimetidine, R = ranitidine
ctrl character P = placebo, AA = antacids, UT = usual treatment
nti numeric number of patients in treatment group
b.xti numeric number of patients in treatment group with persistent or recurrent bleedings
o.xti numeric number of patients in treatment group in need of operation
d.xti numeric number of patients in treatment group that died
nci numeric number of patients in control group
b.xci numeric number of patients in control group with persistent or recurrent bleedings
o.xci numeric number of patients in control group in need of operation
d.xci numeric number of patients in control group that died

Details

The data were obtained from Tables 1 and 2 in Collins and Langman (1985). The authors used Peto's (one-step) method for meta-analyzing the 27 trials. This approach is implemented in the rma.peto function. Using the same dataset, van Houwelingen, Zwinderman, and Stijnen (1993) describe some alternative approaches for analyzing these data, including fixed- and random-effects conditional logistic models. Those are implemented in the rma.glmm function.

Concepts

medicine, odds ratios, Peto's method, generalized linear models

Author(s)

Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org

Source

Collins, R., & Langman, M. (1985). Treatment with histamine H2 antagonists in acute upper gastrointestinal hemorrhage. New England Journal of Medicine, 313(11), 660–666. https://doi.org/10.1056/NEJM198509123131104

References

van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T. (1993). A bivariate approach to meta-analysis. Statistics in Medicine, 12(24), 2273–2284. https://doi.org/10.1002/sim.4780122405

Examples

### copy data into 'dat' and examine data
dat <- dat.collins1985a
dat

## Not run: 

### load metafor package
library(metafor)

### meta-analysis of log ORs using Peto's method (outcome: persistent or recurrent bleedings)
res <- rma.peto(ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat)
print(res, digits=2)

### meta-analysis of log ORs using a conditional logistic regression model (FE model)
res <- rma.glmm(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
                model="CM.EL", method="FE")
summary(res)
predict(res, transf=exp, digits=2)

### plot the likelihoods of the odds ratios
llplot(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
       lwd=1, refline=NA, xlim=c(-4,4), drop00=FALSE)

### meta-analysis of log odds ratios using a conditional logistic regression model (RE model)
res <- rma.glmm(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
                model="CM.EL", method="ML")
summary(res)
predict(res, transf=exp, digits=2)

### meta-analysis of log ORs using Peto's method (outcome: need for surgery)
res <- rma.peto(ai=o.xti, n1i=nti, ci=o.xci, n2i=nci, data=dat)
print(res, digits=2)

### meta-analysis of log ORs using Peto's method (outcome: death)
res <- rma.peto(ai=d.xti, n1i=nti, ci=d.xci, n2i=nci, data=dat)
print(res, digits=2)


## End(Not run)

metadat documentation built on April 6, 2022, 5:08 p.m.