dat.collins1985a | R Documentation |
Results from studies examining the effectiveness of histamine H2 antagonists (cimetidine or ranitidine) in treating patients with acute upper gastrointestinal hemorrhage.
dat.collins1985a
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 |
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.
medicine, odds ratios, Peto's method, generalized linear models
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
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
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
### 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)
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